diff --git a/docs/paper/reductions.typ b/docs/paper/reductions.typ
index 399057804..e46c53bca 100644
--- a/docs/paper/reductions.typ
+++ b/docs/paper/reductions.typ
@@ -114,6 +114,7 @@
   "SubgraphIsomorphism": [Subgraph Isomorphism],
   "PartitionIntoTriangles": [Partition Into Triangles],
   "FlowShopScheduling": [Flow Shop Scheduling],
+  "MultiprocessorScheduling": [Multiprocessor Scheduling],
   "MinimumTardinessSequencing": [Minimum Tardiness Sequencing],
   "SequencingWithinIntervals": [Sequencing Within Intervals],
   "DirectedTwoCommodityIntegralFlow": [Directed Two-Commodity Integral Flow],
@@ -2377,6 +2378,75 @@ NP-completeness was established by Garey, Johnson, and Stockmeyer @gareyJohnsonS
   ) <fig:flowshop>
 ]
 
+#{
+  let x = load-model-example("MultiprocessorScheduling")
+  let lengths = x.instance.lengths
+  let num-processors = x.instance.num_processors
+  let deadline = x.instance.deadline
+  let assignment = x.optimal.at(0).config
+  let tasks-by-processor = range(num-processors).map(p =>
+    range(lengths.len()).filter(i => assignment.at(i) == p)
+  )
+  let loads = tasks-by-processor.map(tasks => tasks.map(i => lengths.at(i)).sum())
+  let max-x = (num-processors - 1) * 1.8 + 1.0
+  [
+    #problem-def("MultiprocessorScheduling")[
+      Given a finite set $T$ of tasks with processing lengths $ell: T -> ZZ^+$, a number $m in ZZ^+$ of identical processors, and a deadline $D in ZZ^+$, determine whether there exists an assignment $p: T -> {1, dots, m}$ such that for every processor $i in {1, dots, m}$ we have $sum_(t in T: p(t) = i) ell(t) <= D$.
+    ][
+      Multiprocessor Scheduling is problem SS8 in Garey & Johnson @garey1979. Their original formulation uses start times on identical processors, but because tasks are independent and non-preemptive, any feasible schedule can be packed contiguously on each processor. The model implemented here therefore uses processor-assignment variables, and feasibility reduces to checking that every processor's total load is at most $D$. For fixed $m$, dynamic programming over load vectors gives pseudo-polynomial algorithms; for general $m$, the best known exact algorithm runs in $O^*(2^n)$ time via inclusion-exclusion over set partitions @bjorklund2009.
+
+      *Example.* Let $T = {t_1, dots, t_5}$ with lengths $(4, 5, 3, 2, 6)$, $m = 2$, and $D = 10$. The satisfying assignment $(1, 2, 2, 2, 1)$ places $t_1$ and $t_5$ on processor 1 and $t_2, t_3, t_4$ on processor 2. The verifier computes the processor loads $4 + 6 = 10$ and $5 + 3 + 2 = 10$, so both meet the deadline exactly.
+
+      #figure({
+        canvas(length: 1cm, {
+          let scale = 0.25
+          let width = 1.0
+          let gap = 0.8
+          let colors = (
+            rgb("#4e79a7"),
+            rgb("#e15759"),
+            rgb("#76b7b2"),
+            rgb("#f28e2b"),
+            rgb("#59a14f"),
+          )
+
+          for p in range(num-processors) {
+            let x0 = p * (width + gap)
+            draw.rect((x0, 0), (x0 + width, deadline * scale), stroke: 0.8pt + black)
+            let y = 0
+            for task in tasks-by-processor.at(p) {
+              let len = lengths.at(task)
+              let col = colors.at(task)
+              draw.rect(
+                (x0, y),
+                (x0 + width, y + len * scale),
+                fill: col.transparentize(25%),
+                stroke: 0.4pt + col,
+              )
+              draw.content(
+                (x0 + width / 2, y + len * scale / 2),
+                text(7pt, fill: white)[$t_#(task + 1)$],
+              )
+              y += len * scale
+            }
+            draw.content((x0 + width / 2, -0.3), text(8pt)[$P_#(p + 1)$])
+            draw.content((x0 + width / 2, deadline * scale + 0.25), text(7pt)[$L_#(p + 1) = #loads.at(p)$])
+          }
+
+          draw.line(
+            (-0.15, deadline * scale),
+            (max-x + 0.15, deadline * scale),
+            stroke: (dash: "dashed", paint: luma(150), thickness: 0.5pt),
+          )
+          draw.content((-0.45, deadline * scale), text(7pt)[$D$])
+        })
+      },
+      caption: [Canonical Multiprocessor Scheduling instance with 5 tasks on 2 processors. Stacked blocks show the satisfying assignment $(1, 2, 2, 2, 1)$; both processor loads equal the deadline $D = 10$.],
+      ) <fig:multiprocessor-scheduling>
+    ]
+  ]
+}
+
 #{
   let x = load-model-example("SequencingWithinIntervals")
   let ntasks = x.instance.lengths.len()
diff --git a/docs/paper/references.bib b/docs/paper/references.bib
index 34fc92a17..e85884d5e 100644
--- a/docs/paper/references.bib
+++ b/docs/paper/references.bib
@@ -40,6 +40,16 @@ @article{shang2018
   doi     = {10.1016/j.cor.2017.10.015}
 }
 
+@article{brucker1977,
+  author  = {Peter Brucker and Jan Karel Lenstra and Alexander H. G. Rinnooy Kan},
+  title   = {Complexity of Machine Scheduling Problems},
+  journal = {Annals of Discrete Mathematics},
+  volume  = {1},
+  pages   = {343--362},
+  year    = {1977},
+  doi     = {10.1016/S0167-5060(08)70743-X}
+}
+
 @inproceedings{karp1972,
   author    = {Richard M. Karp},
   title     = {Reducibility among Combinatorial Problems},
diff --git a/docs/src/cli.md b/docs/src/cli.md
index 404c03ef1..563727f23 100644
--- a/docs/src/cli.md
+++ b/docs/src/cli.md
@@ -515,8 +515,9 @@ Source evaluation: Valid(2)
 ```
 
 > **Note:** The ILP solver requires a reduction path from the target problem to ILP.
-> Some problems (e.g., BoundedComponentSpanningForest, LengthBoundedDisjointPaths) do not currently have one, so use
-> `pred solve <file> --solver brute-force` for these.
+> Some problems do not currently have one. Examples include BoundedComponentSpanningForest,
+> LengthBoundedDisjointPaths, QUBO, SpinGlass, MaxCut, CircuitSAT, and MultiprocessorScheduling.
+> Use `pred solve <file> --solver brute-force` for these, or reduce to a problem that supports ILP first.
 > For other problems, use `pred path <PROBLEM> ILP` to check whether an ILP reduction path exists.
 
 ## Shell Completions
diff --git a/problemreductions-cli/src/cli.rs b/problemreductions-cli/src/cli.rs
index 2ed085d11..eadbfc925 100644
--- a/problemreductions-cli/src/cli.rs
+++ b/problemreductions-cli/src/cli.rs
@@ -243,6 +243,7 @@ Flags by problem type:
   BMF                             --matrix (0/1), --rank
   SteinerTree                     --graph, --edge-weights, --terminals
   CVP                             --basis, --target-vec [--bounds]
+  MultiprocessorScheduling        --lengths, --num-processors, --deadline
   SequencingWithinIntervals       --release-times, --deadlines, --lengths
   OptimalLinearArrangement        --graph, --bound
   RuralPostman (RPP)              --graph, --edge-weights, --required-edges, --bound
@@ -276,6 +277,7 @@ Examples:
   pred create MIS/KingsSubgraph --positions \"0,0;1,0;1,1;0,1\"
   pred create MIS/UnitDiskGraph --positions \"0,0;1,0;0.5,0.8\" --radius 1.5
   pred create MIS --random --num-vertices 10 --edge-prob 0.3
+  pred create MultiprocessorScheduling --lengths 4,5,3,2,6 --num-processors 2 --deadline 10
   pred create BiconnectivityAugmentation --graph 0-1,1-2,2-3 --potential-edges 0-2:3,0-3:4,1-3:2 --budget 5
   pred create FVS --arcs \"0>1,1>2,2>0\" --weights 1,1,1
   pred create UndirectedTwoCommodityIntegralFlow --graph 0-2,1-2,2-3 --capacities 1,1,2 --source-1 0 --sink-1 3 --source-2 1 --sink-2 3 --requirement-1 1 --requirement-2 1
@@ -432,7 +434,7 @@ pub struct CreateArgs {
     /// Release times for SequencingWithinIntervals (comma-separated, e.g., "0,0,5")
     #[arg(long)]
     pub release_times: Option<String>,
-    /// Processing lengths for SequencingWithinIntervals (comma-separated, e.g., "3,1,1")
+    /// Processing lengths (comma-separated, e.g., "4,5,3,2,6")
     #[arg(long)]
     pub lengths: Option<String>,
     /// Terminal vertices for SteinerTree or MinimumMultiwayCut (comma-separated indices, e.g., "0,2,4")
@@ -474,10 +476,10 @@ pub struct CreateArgs {
     /// Task lengths for FlowShopScheduling (semicolon-separated rows: "3,4,2;2,3,5;4,1,3")
     #[arg(long)]
     pub task_lengths: Option<String>,
-    /// Deadline for FlowShopScheduling
+    /// Deadline for FlowShopScheduling or MultiprocessorScheduling
     #[arg(long)]
     pub deadline: Option<u64>,
-    /// Number of processors/machines for FlowShopScheduling
+    /// Number of processors/machines for FlowShopScheduling or MultiprocessorScheduling
     #[arg(long)]
     pub num_processors: Option<usize>,
     /// Alphabet size for SCS (optional; inferred from max symbol + 1 if omitted)
diff --git a/problemreductions-cli/src/commands/create.rs b/problemreductions-cli/src/commands/create.rs
index 695c1cd88..2831a9ef5 100644
--- a/problemreductions-cli/src/commands/create.rs
+++ b/problemreductions-cli/src/commands/create.rs
@@ -14,7 +14,8 @@ use problemreductions::models::graph::{
 };
 use problemreductions::models::misc::{
     BinPacking, FlowShopScheduling, LongestCommonSubsequence, MinimumTardinessSequencing,
-    PaintShop, SequencingWithinIntervals, ShortestCommonSupersequence, SubsetSum,
+    MultiprocessorScheduling, PaintShop, SequencingWithinIntervals, ShortestCommonSupersequence,
+    SubsetSum,
 };
 use problemreductions::models::BiconnectivityAugmentation;
 use problemreductions::prelude::*;
@@ -226,7 +227,7 @@ fn type_format_hint(type_name: &str, graph_type: Option<&str>) -> &'static str {
             Some("UnitDiskGraph") => "float positions: \"0.0,0.0;1.0,0.0\"",
             _ => "edge list: 0-1,1-2,2-3",
         },
-        "Vec<u64>" => "comma-separated integers: 1,2,3",
+        "Vec<u64>" => "comma-separated integers: 4,5,3,2,6",
         "Vec<W>" => "comma-separated: 1,2,3",
         "Vec<usize>" => "comma-separated indices: 0,2,4",
         "Vec<(usize, usize, W)>" | "Vec<(usize,usize,W)>" => {
@@ -288,6 +289,7 @@ fn example_for(canonical: &str, graph_type: Option<&str>) -> &'static str {
         }
         "PartitionIntoTriangles" => "--graph 0-1,1-2,0-2",
         "Factoring" => "--target 15 --m 4 --n 4",
+        "MultiprocessorScheduling" => "--lengths 4,5,3,2,6 --num-processors 2 --deadline 10",
         "MinimumMultiwayCut" => "--graph 0-1,1-2,2-3 --terminals 0,2 --edge-weights 1,1,1",
         "SequencingWithinIntervals" => "--release-times 0,0,5 --deadlines 11,11,6 --lengths 3,1,1",
         "SteinerTree" => "--graph 0-1,1-2,1-3,3-4 --edge-weights 2,2,1,1 --terminals 0,2,4",
@@ -1286,6 +1288,34 @@ pub fn create(args: &CreateArgs, out: &OutputConfig) -> Result<()> {
             )
         }
 
+        // MultiprocessorScheduling
+        "MultiprocessorScheduling" => {
+            let usage = "Usage: pred create MultiprocessorScheduling --lengths 4,5,3,2,6 --num-processors 2 --deadline 10";
+            let lengths_str = args.lengths.as_deref().ok_or_else(|| {
+                anyhow::anyhow!(
+                    "MultiprocessorScheduling requires --lengths, --num-processors, and --deadline\n\n{usage}"
+                )
+            })?;
+            let num_processors = args.num_processors.ok_or_else(|| {
+                anyhow::anyhow!("MultiprocessorScheduling requires --num-processors\n\n{usage}")
+            })?;
+            if num_processors == 0 {
+                bail!("MultiprocessorScheduling requires --num-processors > 0\n\n{usage}");
+            }
+            let deadline = args.deadline.ok_or_else(|| {
+                anyhow::anyhow!("MultiprocessorScheduling requires --deadline\n\n{usage}")
+            })?;
+            let lengths: Vec<u64> = util::parse_comma_list(lengths_str)?;
+            (
+                ser(MultiprocessorScheduling::new(
+                    lengths,
+                    num_processors,
+                    deadline,
+                ))?,
+                resolved_variant.clone(),
+            )
+        }
+
         // MinimumMultiwayCut
         "MinimumMultiwayCut" => {
             let (graph, _) = parse_graph(args).map_err(|e| {
@@ -1708,7 +1738,6 @@ pub fn create(args: &CreateArgs, out: &OutputConfig) -> Result<()> {
                 resolved_variant.clone(),
             )
         }
-
         _ => bail!("{}", crate::problem_name::unknown_problem_error(canonical)),
     };
 
diff --git a/problemreductions-cli/src/commands/inspect.rs b/problemreductions-cli/src/commands/inspect.rs
index 3a5d37cad..c8fb7c27c 100644
--- a/problemreductions-cli/src/commands/inspect.rs
+++ b/problemreductions-cli/src/commands/inspect.rs
@@ -40,8 +40,17 @@ fn inspect_problem(pj: &ProblemJson, out: &OutputConfig) -> Result<()> {
     }
     text.push_str(&format!("Variables: {}\n", problem.num_variables_dyn()));
 
-    // Solvers
-    text.push_str("Solvers: ilp (default), brute-force\n");
+    let solvers = if problem.supports_ilp_solver() {
+        vec!["ilp", "brute-force"]
+    } else {
+        vec!["brute-force"]
+    };
+    let solver_summary = if solvers.first() == Some(&"ilp") {
+        "ilp (default), brute-force".to_string()
+    } else {
+        "brute-force".to_string()
+    };
+    text.push_str(&format!("Solvers: {solver_summary}\n"));
 
     // Reductions
     let outgoing = graph.outgoing_reductions(name);
@@ -56,7 +65,7 @@ fn inspect_problem(pj: &ProblemJson, out: &OutputConfig) -> Result<()> {
         "variant": variant,
         "size_fields": size_fields,
         "num_variables": problem.num_variables_dyn(),
-        "solvers": ["ilp", "brute-force"],
+        "solvers": solvers,
         "reduces_to": targets,
     });
 
diff --git a/problemreductions-cli/src/commands/solve.rs b/problemreductions-cli/src/commands/solve.rs
index bdbc1db66..663ee33b3 100644
--- a/problemreductions-cli/src/commands/solve.rs
+++ b/problemreductions-cli/src/commands/solve.rs
@@ -97,7 +97,7 @@ fn solve_problem(
             result
         }
         "ilp" => {
-            let result = problem.solve_with_ilp()?;
+            let result = problem.solve_with_ilp().map_err(add_ilp_solver_hint)?;
             let solver_desc = if name == "ILP" {
                 "ilp".to_string()
             } else {
@@ -139,7 +139,7 @@ fn solve_bundle(bundle: ReductionBundle, solver_name: &str, out: &OutputConfig)
     // 2. Solve the target problem
     let target_result = match solver_name {
         "brute-force" => target.solve_brute_force()?,
-        "ilp" => target.solve_with_ilp()?,
+        "ilp" => target.solve_with_ilp().map_err(add_ilp_solver_hint)?,
         _ => unreachable!(),
     };
 
@@ -200,3 +200,14 @@ fn solve_bundle(bundle: ReductionBundle, solver_name: &str, out: &OutputConfig)
     }
     result
 }
+
+fn add_ilp_solver_hint(err: anyhow::Error) -> anyhow::Error {
+    let message = err.to_string();
+    if message.starts_with("No reduction path from ") && message.ends_with(" to ILP") {
+        anyhow::anyhow!(
+            "{message}\n\nHint: try `--solver brute-force` for direct exhaustive search on small instances."
+        )
+    } else {
+        err
+    }
+}
diff --git a/problemreductions-cli/src/dispatch.rs b/problemreductions-cli/src/dispatch.rs
index 95a50fb65..5d63a9f77 100644
--- a/problemreductions-cli/src/dispatch.rs
+++ b/problemreductions-cli/src/dispatch.rs
@@ -47,6 +47,11 @@ impl LoadedProblem {
         Ok(SolveResult { config, evaluation })
     }
 
+    pub fn supports_ilp_solver(&self) -> bool {
+        let name = self.problem_name();
+        name == "ILP" || self.best_ilp_reduction_path().is_some()
+    }
+
     /// Solve using the ILP solver. If the problem is not ILP, auto-reduce to ILP first.
     pub fn solve_with_ilp(&self) -> Result<SolveResult> {
         let name = self.problem_name();
@@ -54,7 +59,26 @@ impl LoadedProblem {
             return solve_ilp(self.as_any());
         }
 
-        // Auto-reduce to ILP, solve, and map solution back
+        let reduction_path = self.best_ilp_reduction_path().ok_or_else(|| {
+            anyhow::anyhow!(
+                "No reduction path from {} to ILP. Try `--solver brute-force`, or reduce to a problem that supports ILP.",
+                name
+            )
+        })?;
+        let graph = ReductionGraph::new();
+
+        let chain = graph
+            .reduce_along_path(&reduction_path, self.as_any())
+            .ok_or_else(|| anyhow::anyhow!("Failed to execute reduction chain to ILP"))?;
+
+        let ilp_result = solve_ilp(chain.target_problem_any())?;
+        let config = chain.extract_solution(&ilp_result.config);
+        let evaluation = self.evaluate_dyn(&config);
+        Ok(SolveResult { config, evaluation })
+    }
+
+    fn best_ilp_reduction_path(&self) -> Option<problemreductions::rules::ReductionPath> {
+        let name = self.problem_name();
         let source_variant = self.variant_map();
         let graph = ReductionGraph::new();
         let ilp_variants = graph.variants_for("ILP");
@@ -62,7 +86,7 @@ impl LoadedProblem {
 
         let mut best_path = None;
         for dv in &ilp_variants {
-            if let Some(p) = graph.find_cheapest_path(
+            if let Some(path) = graph.find_cheapest_path(
                 name,
                 &source_variant,
                 "ILP",
@@ -70,30 +94,16 @@ impl LoadedProblem {
                 &input_size,
                 &MinimizeSteps,
             ) {
-                let is_better = best_path
-                    .as_ref()
-                    .is_none_or(|bp: &problemreductions::rules::ReductionPath| p.len() < bp.len());
+                let is_better = best_path.as_ref().is_none_or(
+                    |current: &problemreductions::rules::ReductionPath| path.len() < current.len(),
+                );
                 if is_better {
-                    best_path = Some(p);
+                    best_path = Some(path);
                 }
             }
         }
 
-        let reduction_path = best_path.ok_or_else(|| {
-            anyhow::anyhow!(
-                "No reduction path from {} to ILP. Try `--solver brute-force`, or reduce to a problem that supports ILP.",
-                name
-            )
-        })?;
-
-        let chain = graph
-            .reduce_along_path(&reduction_path, self.as_any())
-            .ok_or_else(|| anyhow::anyhow!("Failed to execute reduction chain to ILP"))?;
-
-        let ilp_result = solve_ilp(chain.target_problem_any())?;
-        let config = chain.extract_solution(&ilp_result.config);
-        let evaluation = self.evaluate_dyn(&config);
-        Ok(SolveResult { config, evaluation })
+        best_path
     }
 }
 
@@ -249,4 +259,26 @@ mod tests {
         let json = serialize_any_problem("BinPacking", &variant, &problem as &dyn Any).unwrap();
         assert_eq!(json, serde_json::to_value(&problem).unwrap());
     }
+
+    #[test]
+    fn test_load_problem_rejects_zero_processor_multiprocessor_scheduling() {
+        let loaded = load_problem(
+            "MultiprocessorScheduling",
+            &BTreeMap::new(),
+            serde_json::json!({
+                "lengths": [1, 2],
+                "num_processors": 0,
+                "deadline": 5
+            }),
+        );
+        assert!(
+            loaded.is_err(),
+            "zero-processor instance should be rejected"
+        );
+        let err = loaded.err().unwrap();
+        assert!(
+            err.to_string().contains("expected positive integer, got 0"),
+            "unexpected error: {err}"
+        );
+    }
 }
diff --git a/problemreductions-cli/tests/cli_tests.rs b/problemreductions-cli/tests/cli_tests.rs
index 803009433..76058569b 100644
--- a/problemreductions-cli/tests/cli_tests.rs
+++ b/problemreductions-cli/tests/cli_tests.rs
@@ -886,6 +886,68 @@ fn test_create_mis() {
     std::fs::remove_file(&output_file).ok();
 }
 
+#[test]
+fn test_create_multiprocessor_scheduling() {
+    let output_file = std::env::temp_dir().join("pred_test_create_multiprocessor_scheduling.json");
+    let output = pred()
+        .args([
+            "-o",
+            output_file.to_str().unwrap(),
+            "create",
+            "MultiprocessorScheduling",
+            "--lengths",
+            "4,5,3,2,6",
+            "--num-processors",
+            "2",
+            "--deadline",
+            "10",
+        ])
+        .output()
+        .unwrap();
+    assert!(
+        output.status.success(),
+        "stderr: {}",
+        String::from_utf8_lossy(&output.stderr)
+    );
+
+    let content = std::fs::read_to_string(&output_file).unwrap();
+    let json: serde_json::Value = serde_json::from_str(&content).unwrap();
+    assert_eq!(json["type"], "MultiprocessorScheduling");
+    assert_eq!(json["data"]["lengths"], serde_json::json!([4, 5, 3, 2, 6]));
+    assert_eq!(json["data"]["num_processors"], 2);
+    assert_eq!(json["data"]["deadline"], 10);
+
+    std::fs::remove_file(&output_file).ok();
+}
+
+#[test]
+fn test_create_multiprocessor_scheduling_rejects_zero_processors() {
+    let output = pred()
+        .args([
+            "create",
+            "MultiprocessorScheduling",
+            "--lengths",
+            "4,5,3,2,6",
+            "--num-processors",
+            "0",
+            "--deadline",
+            "10",
+        ])
+        .output()
+        .unwrap();
+
+    assert!(!output.status.success());
+    let stderr = String::from_utf8_lossy(&output.stderr);
+    assert!(
+        !stderr.contains("panicked at"),
+        "zero processors should return a user error, got panic output: {stderr}"
+    );
+    assert!(
+        stderr.contains("requires --num-processors > 0"),
+        "expected a validation error for zero processors, got: {stderr}"
+    );
+}
+
 #[test]
 fn test_create_x3c_alias() {
     let output_file = std::env::temp_dir().join("pred_test_create_x3c.json");
@@ -3910,6 +3972,64 @@ fn test_inspect_json_output() {
     std::fs::remove_file(&result_file).ok();
 }
 
+#[test]
+fn test_inspect_multiprocessor_scheduling_reports_only_brute_force_solver() {
+    let problem_file = std::env::temp_dir().join("pred_test_inspect_mps_in.json");
+    let result_file = std::env::temp_dir().join("pred_test_inspect_mps_out.json");
+    let create_out = pred()
+        .args([
+            "-o",
+            problem_file.to_str().unwrap(),
+            "create",
+            "MultiprocessorScheduling",
+            "--lengths",
+            "4,5,3,2,6",
+            "--num-processors",
+            "2",
+            "--deadline",
+            "10",
+        ])
+        .output()
+        .unwrap();
+    assert!(
+        create_out.status.success(),
+        "stderr: {}",
+        String::from_utf8_lossy(&create_out.stderr)
+    );
+
+    let output = pred()
+        .args([
+            "-o",
+            result_file.to_str().unwrap(),
+            "inspect",
+            problem_file.to_str().unwrap(),
+        ])
+        .output()
+        .unwrap();
+    assert!(
+        output.status.success(),
+        "stderr: {}",
+        String::from_utf8_lossy(&output.stderr)
+    );
+
+    let content = std::fs::read_to_string(&result_file).unwrap();
+    let json: serde_json::Value = serde_json::from_str(&content).unwrap();
+    let solvers: Vec<&str> = json["solvers"]
+        .as_array()
+        .expect("solvers should be an array")
+        .iter()
+        .map(|v| v.as_str().unwrap())
+        .collect();
+    assert_eq!(
+        solvers,
+        vec!["brute-force"],
+        "unexpected solvers: {solvers:?}"
+    );
+
+    std::fs::remove_file(&problem_file).ok();
+    std::fs::remove_file(&result_file).ok();
+}
+
 #[test]
 fn test_inspect_undirected_two_commodity_integral_flow_reports_size_fields() {
     let problem_file = std::env::temp_dir().join("pred_test_utcif_inspect_in.json");
@@ -4314,6 +4434,91 @@ fn test_create_factoring_missing_bits() {
     );
 }
 
+#[test]
+fn test_evaluate_multiprocessor_scheduling_rejects_zero_processors_json() {
+    let problem_file =
+        std::env::temp_dir().join("pred_test_eval_multiprocessor_zero_processors.json");
+    std::fs::write(
+        &problem_file,
+        r#"{
+  "type": "MultiprocessorScheduling",
+  "variant": {},
+  "data": {
+    "lengths": [1, 2],
+    "num_processors": 0,
+    "deadline": 5
+  }
+}"#,
+    )
+    .unwrap();
+
+    let output = pred()
+        .args([
+            "evaluate",
+            problem_file.to_str().unwrap(),
+            "--config",
+            "0,0",
+        ])
+        .output()
+        .unwrap();
+    assert!(
+        !output.status.success(),
+        "stdout: {}",
+        String::from_utf8_lossy(&output.stdout)
+    );
+    let stderr = String::from_utf8_lossy(&output.stderr);
+    assert!(
+        stderr.contains("expected positive integer, got 0"),
+        "stderr: {stderr}"
+    );
+
+    std::fs::remove_file(&problem_file).ok();
+}
+
+#[test]
+fn test_solve_multiprocessor_scheduling_default_solver_suggests_brute_force() {
+    let problem_file =
+        std::env::temp_dir().join("pred_test_solve_multiprocessor_default_solver.json");
+    let create_out = pred()
+        .args([
+            "-o",
+            problem_file.to_str().unwrap(),
+            "create",
+            "MultiprocessorScheduling",
+            "--lengths",
+            "4,5,3,2,6",
+            "--num-processors",
+            "2",
+            "--deadline",
+            "10",
+        ])
+        .output()
+        .unwrap();
+    assert!(
+        create_out.status.success(),
+        "stderr: {}",
+        String::from_utf8_lossy(&create_out.stderr)
+    );
+
+    let output = pred()
+        .args(["solve", problem_file.to_str().unwrap()])
+        .output()
+        .unwrap();
+    assert!(
+        !output.status.success(),
+        "stdout: {}",
+        String::from_utf8_lossy(&output.stdout)
+    );
+    let stderr = String::from_utf8_lossy(&output.stderr);
+    assert!(
+        stderr.contains("No reduction path from MultiprocessorScheduling to ILP"),
+        "stderr: {stderr}"
+    );
+    assert!(stderr.contains("--solver brute-force"), "stderr: {stderr}");
+
+    std::fs::remove_file(&problem_file).ok();
+}
+
 // ---- Timeout tests (H3) ----
 
 #[test]
@@ -5095,6 +5300,22 @@ fn test_create_sequencing_within_intervals() {
     std::fs::remove_file(&output_file).ok();
 }
 
+#[test]
+fn test_create_model_example_multiprocessor_scheduling() {
+    let output = pred()
+        .args(["create", "--example", "MultiprocessorScheduling"])
+        .output()
+        .unwrap();
+    assert!(
+        output.status.success(),
+        "stderr: {}",
+        String::from_utf8_lossy(&output.stderr)
+    );
+    let stdout = String::from_utf8(output.stdout).unwrap();
+    let json: serde_json::Value = serde_json::from_str(&stdout).unwrap();
+    assert_eq!(json["type"], "MultiprocessorScheduling");
+}
+
 #[test]
 fn test_create_model_example_minimum_multiway_cut() {
     let output = pred()
diff --git a/src/example_db/fixtures/examples.json b/src/example_db/fixtures/examples.json
index e31260a21..19aa8e565 100644
--- a/src/example_db/fixtures/examples.json
+++ b/src/example_db/fixtures/examples.json
@@ -32,6 +32,7 @@
     {"problem":"MinimumTardinessSequencing","variant":{},"instance":{"deadlines":[2,3,1,4],"num_tasks":4,"precedences":[[0,2]]},"samples":[{"config":[0,0,0,0],"metric":{"Valid":1}}],"optimal":[{"config":[0,0,0,0],"metric":{"Valid":1}},{"config":[0,0,1,0],"metric":{"Valid":1}},{"config":[0,1,0,0],"metric":{"Valid":1}},{"config":[0,2,0,0],"metric":{"Valid":1}},{"config":[1,0,0,0],"metric":{"Valid":1}},{"config":[1,0,1,0],"metric":{"Valid":1}},{"config":[3,0,0,0],"metric":{"Valid":1}}]},
     {"problem":"MinimumVertexCover","variant":{"graph":"SimpleGraph","weight":"i32"},"instance":{"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[1,3,null],[2,3,null],[2,4,null],[3,4,null]],"node_holes":[],"nodes":[null,null,null,null,null]}},"weights":[1,1,1,1,1]},"samples":[{"config":[1,0,0,1,1],"metric":{"Valid":3}}],"optimal":[{"config":[0,1,1,0,1],"metric":{"Valid":3}},{"config":[0,1,1,1,0],"metric":{"Valid":3}},{"config":[1,0,0,1,1],"metric":{"Valid":3}},{"config":[1,0,1,1,0],"metric":{"Valid":3}}]},
     {"problem":"MultipleChoiceBranching","variant":{"weight":"i32"},"instance":{"graph":{"inner":{"edge_property":"directed","edges":[[0,1,null],[0,2,null],[1,3,null],[2,3,null],[1,4,null],[3,5,null],[4,5,null],[2,4,null]],"node_holes":[],"nodes":[null,null,null,null,null,null]}},"partition":[[0,1],[2,3],[4,7],[5,6]],"threshold":10,"weights":[3,2,4,1,2,3,1,3]},"samples":[{"config":[1,0,1,0,0,1,0,1],"metric":true}],"optimal":[{"config":[0,0,1,0,0,1,0,1],"metric":true},{"config":[0,1,1,0,0,0,1,1],"metric":true},{"config":[0,1,1,0,0,1,0,1],"metric":true},{"config":[0,1,1,0,1,1,0,0],"metric":true},{"config":[1,0,0,1,0,1,0,1],"metric":true},{"config":[1,0,1,0,0,0,0,1],"metric":true},{"config":[1,0,1,0,0,0,1,1],"metric":true},{"config":[1,0,1,0,0,1,0,0],"metric":true},{"config":[1,0,1,0,0,1,0,1],"metric":true},{"config":[1,0,1,0,1,0,1,0],"metric":true},{"config":[1,0,1,0,1,1,0,0],"metric":true}]},
+    {"problem":"MultiprocessorScheduling","variant":{},"instance":{"deadline":10,"lengths":[4,5,3,2,6],"num_processors":2},"samples":[{"config":[0,0,0,0,0],"metric":false},{"config":[0,1,1,1,0],"metric":true}],"optimal":[{"config":[0,1,1,1,0],"metric":true}]},
     {"problem":"PaintShop","variant":{},"instance":{"car_labels":["A","B","C"],"is_first":[true,true,false,true,false,false],"num_cars":3,"sequence_indices":[0,1,0,2,1,2]},"samples":[{"config":[0,0,1],"metric":{"Valid":2}}],"optimal":[{"config":[0,0,1],"metric":{"Valid":2}},{"config":[0,1,1],"metric":{"Valid":2}},{"config":[1,0,0],"metric":{"Valid":2}},{"config":[1,1,0],"metric":{"Valid":2}}]},
     {"problem":"PartitionIntoTriangles","variant":{"graph":"SimpleGraph"},"instance":{"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[1,2,null],[3,4,null],[3,5,null],[4,5,null],[0,3,null]],"node_holes":[],"nodes":[null,null,null,null,null,null]}}},"samples":[{"config":[0,0,0,1,1,1],"metric":true}],"optimal":[{"config":[0,0,0,1,1,1],"metric":true},{"config":[1,1,1,0,0,0],"metric":true}]},
     {"problem":"QUBO","variant":{"weight":"f64"},"instance":{"matrix":[[-1.0,2.0,0.0],[0.0,-1.0,2.0],[0.0,0.0,-1.0]],"num_vars":3},"samples":[{"config":[1,0,1],"metric":{"Valid":-2.0}}],"optimal":[{"config":[1,0,1],"metric":{"Valid":-2.0}}]},
@@ -55,18 +56,18 @@
     {"source":{"problem":"KColoring","variant":{"graph":"SimpleGraph","k":"KN"},"instance":{"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,4,null],[0,5,null],[1,2,null],[1,6,null],[2,3,null],[2,7,null],[3,4,null],[3,8,null],[4,9,null],[5,7,null],[5,8,null],[6,8,null],[6,9,null],[7,9,null]],"node_holes":[],"nodes":[null,null,null,null,null,null,null,null,null,null]}},"num_colors":3}},"target":{"problem":"ILP","variant":{"variable":"bool"},"instance":{"constraints":[{"cmp":"Eq","rhs":1.0,"terms":[[0,1.0],[1,1.0],[2,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[3,1.0],[4,1.0],[5,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[6,1.0],[7,1.0],[8,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[9,1.0],[10,1.0],[11,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[12,1.0],[13,1.0],[14,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[15,1.0],[16,1.0],[17,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[18,1.0],[19,1.0],[20,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[21,1.0],[22,1.0],[23,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[24,1.0],[25,1.0],[26,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[27,1.0],[28,1.0],[29,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[0,1.0],[3,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[1,1.0],[4,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[2,1.0],[5,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[0,1.0],[12,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[1,1.0],[13,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[2,1.0],[14,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[0,1.0],[15,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[1,1.0],[16,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[2,1.0],[17,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[3,1.0],[6,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[4,1.0],[7,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[5,1.0],[8,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[3,1.0],[18,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[4,1.0],[19,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[5,1.0],[20,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[6,1.0],[9,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[7,1.0],[10,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[8,1.0],[11,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[6,1.0],[21,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[7,1.0],[22,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[8,1.0],[23,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[9,1.0],[12,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[10,1.0],[13,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[11,1.0],[14,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[9,1.0],[24,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[10,1.0],[25,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[11,1.0],[26,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[12,1.0],[27,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[13,1.0],[28,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[14,1.0],[29,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[15,1.0],[21,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[16,1.0],[22,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[17,1.0],[23,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[15,1.0],[24,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[16,1.0],[25,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[17,1.0],[26,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[18,1.0],[24,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[19,1.0],[25,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[20,1.0],[26,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[18,1.0],[27,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[19,1.0],[28,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[20,1.0],[29,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[21,1.0],[27,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[22,1.0],[28,1.0]]},{"cmp":"Le","rhs":1.0,"terms":[[23,1.0],[29,1.0]]}],"num_vars":30,"objective":[],"sense":"Minimize"}},"solutions":[{"source_config":[0,2,0,1,2,1,1,2,0,0],"target_config":[1,0,0,0,0,1,1,0,0,0,1,0,0,0,1,0,1,0,0,1,0,0,0,1,1,0,0,1,0,0]}]},
     {"source":{"problem":"KColoring","variant":{"graph":"SimpleGraph","k":"KN"},"instance":{"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[1,3,null],[2,3,null],[2,4,null],[3,4,null]],"node_holes":[],"nodes":[null,null,null,null,null]}},"num_colors":3}},"target":{"problem":"QUBO","variant":{"weight":"f64"},"instance":{"matrix":[[-6.0,12.0,12.0,3.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],[0.0,-6.0,12.0,0.0,3.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],[0.0,0.0,-6.0,0.0,0.0,3.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,-6.0,12.0,12.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,-6.0,12.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,-6.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,-6.0,12.0,12.0,3.0,0.0,0.0,3.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0,12.0,0.0,3.0,0.0,0.0,3.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0,0.0,0.0,3.0,0.0,0.0,3.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0,12.0,12.0,3.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0,12.0,0.0,3.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0,0.0,0.0,3.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0,12.0,12.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0,12.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-6.0]],"num_vars":15}},"solutions":[{"source_config":[1,2,2,1,0],"target_config":[0,1,0,0,0,1,0,0,1,0,1,0,1,0,0]}]},
     {"source":{"problem":"KSatisfiability","variant":{"k":"K2"},"instance":{"clauses":[{"literals":[1,2]},{"literals":[-1,3]},{"literals":[-2,4]},{"literals":[-3,-4]}],"num_vars":4}},"target":{"problem":"QUBO","variant":{"weight":"f64"},"instance":{"matrix":[[0.0,1.0,-1.0,0.0],[0.0,0.0,0.0,-1.0],[0.0,0.0,0.0,1.0],[0.0,0.0,0.0,0.0]],"num_vars":4}},"solutions":[{"source_config":[0,1,0,1],"target_config":[0,1,0,1]}]},
-    {"source":{"problem":"KSatisfiability","variant":{"k":"K3"},"instance":{"clauses":[{"literals":[1,2,-3]},{"literals":[-1,3,4]},{"literals":[2,-4,5]},{"literals":[-2,3,-5]},{"literals":[1,-3,5]},{"literals":[-1,-2,4]},{"literals":[3,-4,-5]}],"num_vars":5}},"target":{"problem":"QUBO","variant":{"weight":"f64"},"instance":{"matrix":[[0.0,4.0,-4.0,0.0,0.0,4.0,-4.0,0.0,0.0,4.0,-4.0,0.0],[0.0,0.0,-2.0,-2.0,0.0,4.0,0.0,4.0,-4.0,0.0,-4.0,0.0],[0.0,0.0,2.0,-2.0,0.0,1.0,4.0,0.0,4.0,-4.0,0.0,4.0],[0.0,0.0,0.0,4.0,0.0,0.0,-1.0,-4.0,0.0,0.0,-1.0,-4.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,-1.0,1.0,-1.0,0.0,1.0],[0.0,0.0,0.0,0.0,0.0,-2.0,0.0,0.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0]],"num_vars":12}},"solutions":[{"source_config":[0,0,0,0,0],"target_config":[0,0,0,0,0,1,0,0,0,0,0,0]}]},
+    {"source":{"problem":"KSatisfiability","variant":{"k":"K3"},"instance":{"clauses":[{"literals":[1,2,-3]},{"literals":[-1,3,4]},{"literals":[2,-4,5]},{"literals":[-2,3,-5]},{"literals":[1,-3,5]},{"literals":[-1,-2,4]},{"literals":[3,-4,-5]}],"num_vars":5}},"target":{"problem":"QUBO","variant":{"weight":"f64"},"instance":{"matrix":[[0.0,4.0,-4.0,0.0,0.0,4.0,-4.0,0.0,0.0,4.0,-4.0,0.0],[0.0,0.0,-2.0,-2.0,0.0,4.0,0.0,4.0,-4.0,0.0,-4.0,0.0],[0.0,0.0,2.0,-2.0,0.0,1.0,4.0,0.0,4.0,-4.0,0.0,4.0],[0.0,0.0,0.0,4.0,0.0,0.0,-1.0,-4.0,0.0,0.0,-1.0,-4.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,-1.0,1.0,-1.0,0.0,1.0],[0.0,0.0,0.0,0.0,0.0,-2.0,0.0,0.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0]],"num_vars":12}},"solutions":[{"source_config":[1,1,1,1,1],"target_config":[1,1,1,1,1,0,0,0,0,0,1,0]}]},
     {"source":{"problem":"KSatisfiability","variant":{"k":"K3"},"instance":{"clauses":[{"literals":[1,2,3]},{"literals":[-1,-2,3]}],"num_vars":3}},"target":{"problem":"SubsetSum","variant":{},"instance":{"sizes":["10010","10001","1010","1001","111","100","10","20","1","2"],"target":"11144"}},"solutions":[{"source_config":[0,0,1],"target_config":[0,1,0,1,1,0,1,1,1,0]}]},
     {"source":{"problem":"KSatisfiability","variant":{"k":"KN"},"instance":{"clauses":[{"literals":[1,-2,3]},{"literals":[-1,3,4]},{"literals":[2,-3,-4]}],"num_vars":4}},"target":{"problem":"Satisfiability","variant":{},"instance":{"clauses":[{"literals":[1,-2,3]},{"literals":[-1,3,4]},{"literals":[2,-3,-4]}],"num_vars":4}},"solutions":[{"source_config":[1,1,1,0],"target_config":[1,1,1,0]}]},
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@@ -76,18 +77,18 @@
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+    {"source":{"problem":"SpinGlass","variant":{"graph":"SimpleGraph","weight":"i32"},"instance":{"couplings":[1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1],"fields":[0,0,0,0,0,0,0,0,0,0],"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,4,null],[0,5,null],[1,2,null],[1,6,null],[2,3,null],[2,7,null],[3,4,null],[3,8,null],[4,9,null],[5,7,null],[5,8,null],[6,8,null],[6,9,null],[7,9,null]],"node_holes":[],"nodes":[null,null,null,null,null,null,null,null,null,null]}}}},"target":{"problem":"MaxCut","variant":{"graph":"SimpleGraph","weight":"i32"},"instance":{"edge_weights":[1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1],"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,4,null],[0,5,null],[1,2,null],[1,6,null],[2,3,null],[2,7,null],[3,4,null],[3,8,null],[4,9,null],[5,7,null],[5,8,null],[6,8,null],[6,9,null],[7,9,null]],"node_holes":[],"nodes":[null,null,null,null,null,null,null,null,null,null]}}}},"solutions":[{"source_config":[0,1,1,0,0,1,0,0,1,0],"target_config":[0,1,1,0,0,1,0,0,1,0]}]},
+    {"source":{"problem":"TravelingSalesman","variant":{"graph":"SimpleGraph","weight":"i32"},"instance":{"edge_weights":[10,15,20,35,25,30],"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[0,3,null],[1,2,null],[1,3,null],[2,3,null]],"node_holes":[],"nodes":[null,null,null,null]}}}},"target":{"problem":"ILP","variant":{"variable":"bool"},"instance":{"constraints":[{"cmp":"Eq","rhs":1.0,"terms":[[0,1.0],[1,1.0],[2,1.0],[3,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[4,1.0],[5,1.0],[6,1.0],[7,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[8,1.0],[9,1.0],[10,1.0],[11,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[12,1.0],[13,1.0],[14,1.0],[15,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[0,1.0],[4,1.0],[8,1.0],[12,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[1,1.0],[5,1.0],[9,1.0],[13,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[2,1.0],[6,1.0],[10,1.0],[14,1.0]]},{"cmp":"Eq","rhs":1.0,"terms":[[3,1.0],[7,1.0],[11,1.0],[15,1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[16,1.0],[0,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[16,1.0],[5,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[16,1.0],[0,-1.0],[5,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[17,1.0],[4,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[17,1.0],[1,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[17,1.0],[4,-1.0],[1,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[18,1.0],[1,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[18,1.0],[6,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[18,1.0],[1,-1.0],[6,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[19,1.0],[5,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[19,1.0],[2,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[19,1.0],[5,-1.0],[2,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[20,1.0],[2,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[20,1.0],[7,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[20,1.0],[2,-1.0],[7,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[21,1.0],[6,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[21,1.0],[3,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[21,1.0],[6,-1.0],[3,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[22,1.0],[3,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[22,1.0],[4,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[22,1.0],[3,-1.0],[4,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[23,1.0],[7,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[23,1.0],[0,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[23,1.0],[7,-1.0],[0,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[24,1.0],[0,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[24,1.0],[9,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[24,1.0],[0,-1.0],[9,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[25,1.0],[8,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[25,1.0],[1,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[25,1.0],[8,-1.0],[1,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[26,1.0],[1,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[26,1.0],[10,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[26,1.0],[1,-1.0],[10,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[27,1.0],[9,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[27,1.0],[2,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[27,1.0],[9,-1.0],[2,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[28,1.0],[2,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[28,1.0],[11,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[28,1.0],[2,-1.0],[11,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[29,1.0],[10,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[29,1.0],[3,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[29,1.0],[10,-1.0],[3,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[30,1.0],[3,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[30,1.0],[8,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[30,1.0],[3,-1.0],[8,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[31,1.0],[11,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[31,1.0],[0,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[31,1.0],[11,-1.0],[0,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[32,1.0],[0,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[32,1.0],[13,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[32,1.0],[0,-1.0],[13,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[33,1.0],[12,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[33,1.0],[1,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[33,1.0],[12,-1.0],[1,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[34,1.0],[1,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[34,1.0],[14,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[34,1.0],[1,-1.0],[14,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[35,1.0],[13,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[35,1.0],[2,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[35,1.0],[13,-1.0],[2,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[36,1.0],[2,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[36,1.0],[15,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[36,1.0],[2,-1.0],[15,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[37,1.0],[14,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[37,1.0],[3,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[37,1.0],[14,-1.0],[3,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[38,1.0],[3,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[38,1.0],[12,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[38,1.0],[3,-1.0],[12,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[39,1.0],[15,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[39,1.0],[0,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[39,1.0],[15,-1.0],[0,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[40,1.0],[4,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[40,1.0],[9,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[40,1.0],[4,-1.0],[9,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[41,1.0],[8,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[41,1.0],[5,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[41,1.0],[8,-1.0],[5,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[42,1.0],[5,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[42,1.0],[10,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[42,1.0],[5,-1.0],[10,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[43,1.0],[9,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[43,1.0],[6,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[43,1.0],[9,-1.0],[6,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[44,1.0],[6,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[44,1.0],[11,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[44,1.0],[6,-1.0],[11,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[45,1.0],[10,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[45,1.0],[7,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[45,1.0],[10,-1.0],[7,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[46,1.0],[7,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[46,1.0],[8,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[46,1.0],[7,-1.0],[8,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[47,1.0],[11,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[47,1.0],[4,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[47,1.0],[11,-1.0],[4,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[48,1.0],[4,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[48,1.0],[13,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[48,1.0],[4,-1.0],[13,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[49,1.0],[12,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[49,1.0],[5,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[49,1.0],[12,-1.0],[5,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[50,1.0],[5,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[50,1.0],[14,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[50,1.0],[5,-1.0],[14,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[51,1.0],[13,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[51,1.0],[6,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[51,1.0],[13,-1.0],[6,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[52,1.0],[6,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[52,1.0],[15,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[52,1.0],[6,-1.0],[15,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[53,1.0],[14,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[53,1.0],[7,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[53,1.0],[14,-1.0],[7,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[54,1.0],[7,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[54,1.0],[12,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[54,1.0],[7,-1.0],[12,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[55,1.0],[15,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[55,1.0],[4,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[55,1.0],[15,-1.0],[4,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[56,1.0],[8,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[56,1.0],[13,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[56,1.0],[8,-1.0],[13,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[57,1.0],[12,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[57,1.0],[9,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[57,1.0],[12,-1.0],[9,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[58,1.0],[9,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[58,1.0],[14,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[58,1.0],[9,-1.0],[14,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[59,1.0],[13,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[59,1.0],[10,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[59,1.0],[13,-1.0],[10,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[60,1.0],[10,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[60,1.0],[15,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[60,1.0],[10,-1.0],[15,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[61,1.0],[14,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[61,1.0],[11,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[61,1.0],[14,-1.0],[11,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[62,1.0],[11,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[62,1.0],[12,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[62,1.0],[11,-1.0],[12,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[63,1.0],[15,-1.0]]},{"cmp":"Le","rhs":0.0,"terms":[[63,1.0],[8,-1.0]]},{"cmp":"Ge","rhs":-1.0,"terms":[[63,1.0],[15,-1.0],[8,-1.0]]}],"num_vars":64,"objective":[[16,10.0],[17,10.0],[18,10.0],[19,10.0],[20,10.0],[21,10.0],[22,10.0],[23,10.0],[24,15.0],[25,15.0],[26,15.0],[27,15.0],[28,15.0],[29,15.0],[30,15.0],[31,15.0],[32,20.0],[33,20.0],[34,20.0],[35,20.0],[36,20.0],[37,20.0],[38,20.0],[39,20.0],[40,35.0],[41,35.0],[42,35.0],[43,35.0],[44,35.0],[45,35.0],[46,35.0],[47,35.0],[48,25.0],[49,25.0],[50,25.0],[51,25.0],[52,25.0],[53,25.0],[54,25.0],[55,25.0],[56,30.0],[57,30.0],[58,30.0],[59,30.0],[60,30.0],[61,30.0],[62,30.0],[63,30.0]],"sense":"Minimize"}},"solutions":[{"source_config":[1,1,0,0,1,1],"target_config":[0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0]}]},
+    {"source":{"problem":"TravelingSalesman","variant":{"graph":"SimpleGraph","weight":"i32"},"instance":{"edge_weights":[1,2,3],"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[1,2,null]],"node_holes":[],"nodes":[null,null,null]}}}},"target":{"problem":"QUBO","variant":{"weight":"f64"},"instance":{"matrix":[[-14.0,14.0,14.0,14.0,1.0,1.0,14.0,2.0,2.0],[0.0,-14.0,14.0,1.0,14.0,1.0,2.0,14.0,2.0],[0.0,0.0,-14.0,1.0,1.0,14.0,2.0,2.0,14.0],[0.0,0.0,0.0,-14.0,14.0,14.0,14.0,3.0,3.0],[0.0,0.0,0.0,0.0,-14.0,14.0,3.0,14.0,3.0],[0.0,0.0,0.0,0.0,0.0,-14.0,3.0,3.0,14.0],[0.0,0.0,0.0,0.0,0.0,0.0,-14.0,14.0,14.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,-14.0,14.0],[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-14.0]],"num_vars":9}},"solutions":[{"source_config":[1,1,1],"target_config":[0,0,1,0,1,0,1,0,0]}]}
   ]
 }
diff --git a/src/lib.rs b/src/lib.rs
index 90dfc42a4..9904f143b 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -59,7 +59,7 @@ pub mod prelude {
     };
     pub use crate::models::misc::{
         BinPacking, Factoring, FlowShopScheduling, Knapsack, LongestCommonSubsequence,
-        MinimumTardinessSequencing, PaintShop, SequencingWithinIntervals,
+        MinimumTardinessSequencing, MultiprocessorScheduling, PaintShop, SequencingWithinIntervals,
         ShortestCommonSupersequence, SubsetSum,
     };
     pub use crate::models::set::{
diff --git a/src/models/misc/mod.rs b/src/models/misc/mod.rs
index c4b125274..91a1e8b71 100644
--- a/src/models/misc/mod.rs
+++ b/src/models/misc/mod.rs
@@ -5,6 +5,7 @@
 //! - [`Factoring`]: Integer factorization
 //! - [`FlowShopScheduling`]: Flow Shop Scheduling (meet deadline on m processors)
 //! - [`Knapsack`]: 0-1 Knapsack (maximize value subject to weight capacity)
+//! - [`MultiprocessorScheduling`]: Schedule tasks on processors to meet a deadline
 //! - [`LongestCommonSubsequence`]: Longest Common Subsequence
 //! - [`MinimumTardinessSequencing`]: Minimize tardy tasks in single-machine scheduling
 //! - [`PaintShop`]: Minimize color switches in paint shop scheduling
@@ -18,6 +19,7 @@ mod flow_shop_scheduling;
 mod knapsack;
 mod longest_common_subsequence;
 mod minimum_tardiness_sequencing;
+mod multiprocessor_scheduling;
 pub(crate) mod paintshop;
 mod sequencing_within_intervals;
 pub(crate) mod shortest_common_supersequence;
@@ -29,6 +31,7 @@ pub use flow_shop_scheduling::FlowShopScheduling;
 pub use knapsack::Knapsack;
 pub use longest_common_subsequence::LongestCommonSubsequence;
 pub use minimum_tardiness_sequencing::MinimumTardinessSequencing;
+pub use multiprocessor_scheduling::MultiprocessorScheduling;
 pub use paintshop::PaintShop;
 pub use sequencing_within_intervals::SequencingWithinIntervals;
 pub use shortest_common_supersequence::ShortestCommonSupersequence;
@@ -38,6 +41,7 @@ pub use subset_sum::SubsetSum;
 pub(crate) fn canonical_model_example_specs() -> Vec<crate::example_db::specs::ModelExampleSpec> {
     let mut specs = Vec::new();
     specs.extend(factoring::canonical_model_example_specs());
+    specs.extend(multiprocessor_scheduling::canonical_model_example_specs());
     specs.extend(paintshop::canonical_model_example_specs());
     specs.extend(sequencing_within_intervals::canonical_model_example_specs());
     specs.extend(shortest_common_supersequence::canonical_model_example_specs());
diff --git a/src/models/misc/multiprocessor_scheduling.rs b/src/models/misc/multiprocessor_scheduling.rs
new file mode 100644
index 000000000..f2f44982c
--- /dev/null
+++ b/src/models/misc/multiprocessor_scheduling.rs
@@ -0,0 +1,173 @@
+//! Multiprocessor Scheduling problem implementation.
+//!
+//! The Multiprocessor Scheduling problem asks whether a set of tasks
+//! can be assigned to identical processors such that no processor's
+//! total load exceeds a given deadline.
+
+use crate::registry::{FieldInfo, ProblemSchemaEntry};
+use crate::traits::{Problem, SatisfactionProblem};
+use serde::{Deserialize, Serialize};
+
+inventory::submit! {
+    ProblemSchemaEntry {
+        name: "MultiprocessorScheduling",
+        display_name: "Multiprocessor Scheduling",
+        aliases: &[],
+        dimensions: &[],
+        module_path: module_path!(),
+        description: "Assign tasks to processors so that no processor's load exceeds a deadline",
+        fields: &[
+            FieldInfo { name: "lengths", type_name: "Vec<u64>", description: "Processing time l(t) for each task" },
+            FieldInfo { name: "num_processors", type_name: "usize", description: "Number of identical processors m" },
+            FieldInfo { name: "deadline", type_name: "u64", description: "Global deadline D" },
+        ],
+    }
+}
+
+/// The Multiprocessor Scheduling problem.
+///
+/// Given a set T of tasks with processing times, a number m of identical
+/// processors, and a deadline D, determine whether there exists an assignment
+/// of tasks to processors such that the total load on each processor does
+/// not exceed D.
+///
+/// Because tasks are independent and processors are identical, any feasible
+/// schedule can be packed processor-by-processor without idle gaps. This makes
+/// the scheduling question equivalent to partitioning tasks among processors
+/// with per-processor load at most `D`.
+///
+/// # Representation
+///
+/// Each task has a variable in `{0, ..., m-1}` representing its processor assignment.
+///
+/// # Example
+///
+/// ```
+/// use problemreductions::models::misc::MultiprocessorScheduling;
+/// use problemreductions::{Problem, Solver, BruteForce};
+///
+/// // 5 tasks with lengths [4, 5, 3, 2, 6], 2 processors, deadline 10
+/// let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+/// let solver = BruteForce::new();
+/// let solution = solver.find_satisfying(&problem);
+/// assert!(solution.is_some());
+/// ```
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct MultiprocessorScheduling {
+    /// Processing time for each task.
+    lengths: Vec<u64>,
+    /// Number of identical processors.
+    #[serde(deserialize_with = "positive_usize::deserialize")]
+    num_processors: usize,
+    /// Global deadline.
+    deadline: u64,
+}
+
+impl MultiprocessorScheduling {
+    /// Create a new Multiprocessor Scheduling instance.
+    ///
+    /// # Panics
+    /// Panics if `num_processors` is zero.
+    pub fn new(lengths: Vec<u64>, num_processors: usize, deadline: u64) -> Self {
+        assert!(num_processors > 0, "num_processors must be positive");
+        Self {
+            lengths,
+            num_processors,
+            deadline,
+        }
+    }
+
+    /// Returns the processing times for each task.
+    pub fn lengths(&self) -> &[u64] {
+        &self.lengths
+    }
+
+    /// Returns the number of processors.
+    pub fn num_processors(&self) -> usize {
+        self.num_processors
+    }
+
+    /// Returns the deadline.
+    pub fn deadline(&self) -> u64 {
+        self.deadline
+    }
+
+    /// Returns the number of tasks.
+    pub fn num_tasks(&self) -> usize {
+        self.lengths.len()
+    }
+
+    /// Returns the total processing time of all tasks.
+    pub fn total_length(&self) -> u64 {
+        self.lengths.iter().sum()
+    }
+}
+
+impl Problem for MultiprocessorScheduling {
+    const NAME: &'static str = "MultiprocessorScheduling";
+    type Metric = bool;
+
+    fn variant() -> Vec<(&'static str, &'static str)> {
+        crate::variant_params![]
+    }
+
+    fn dims(&self) -> Vec<usize> {
+        vec![self.num_processors; self.num_tasks()]
+    }
+
+    fn evaluate(&self, config: &[usize]) -> bool {
+        if config.len() != self.num_tasks() {
+            return false;
+        }
+        let m = self.num_processors;
+        if config.iter().any(|&p| p >= m) {
+            return false;
+        }
+        let mut loads = vec![0u64; m];
+        for (i, &processor) in config.iter().enumerate() {
+            loads[processor] += self.lengths[i];
+        }
+        loads.iter().all(|&load| load <= self.deadline)
+    }
+}
+
+impl SatisfactionProblem for MultiprocessorScheduling {}
+
+crate::declare_variants! {
+    default sat MultiprocessorScheduling => "2^num_tasks",
+}
+
+#[cfg(feature = "example-db")]
+pub(crate) fn canonical_model_example_specs() -> Vec<crate::example_db::specs::ModelExampleSpec> {
+    vec![crate::example_db::specs::ModelExampleSpec {
+        id: "multiprocessor_scheduling",
+        build: || {
+            let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+            crate::example_db::specs::explicit_example(
+                problem,
+                vec![vec![0, 0, 0, 0, 0], vec![0, 1, 1, 1, 0]],
+                vec![vec![0, 1, 1, 1, 0]],
+            )
+        },
+    }]
+}
+
+mod positive_usize {
+    use serde::de::Error;
+    use serde::{Deserialize, Deserializer};
+
+    pub fn deserialize<'de, D>(deserializer: D) -> Result<usize, D::Error>
+    where
+        D: Deserializer<'de>,
+    {
+        let value = usize::deserialize(deserializer)?;
+        if value == 0 {
+            return Err(D::Error::custom("expected positive integer, got 0"));
+        }
+        Ok(value)
+    }
+}
+
+#[cfg(test)]
+#[path = "../../unit_tests/models/misc/multiprocessor_scheduling.rs"]
+mod tests;
diff --git a/src/models/mod.rs b/src/models/mod.rs
index 73ca52680..785b96f78 100644
--- a/src/models/mod.rs
+++ b/src/models/mod.rs
@@ -23,8 +23,8 @@ pub use graph::{
 };
 pub use misc::{
     BinPacking, Factoring, FlowShopScheduling, Knapsack, LongestCommonSubsequence,
-    MinimumTardinessSequencing, PaintShop, SequencingWithinIntervals, ShortestCommonSupersequence,
-    SubsetSum,
+    MinimumTardinessSequencing, MultiprocessorScheduling, PaintShop, SequencingWithinIntervals,
+    ShortestCommonSupersequence, SubsetSum,
 };
 pub use set::{
     ComparativeContainment, ExactCoverBy3Sets, MaximumSetPacking, MinimumSetCovering, SetBasis,
diff --git a/src/unit_tests/example_db.rs b/src/unit_tests/example_db.rs
index eaf308f1c..2e90069b3 100644
--- a/src/unit_tests/example_db.rs
+++ b/src/unit_tests/example_db.rs
@@ -67,6 +67,23 @@ fn test_find_model_example_exact_cover_by_3_sets() {
     );
 }
 
+#[test]
+fn test_find_model_example_multiprocessor_scheduling() {
+    let problem = ProblemRef {
+        name: "MultiprocessorScheduling".to_string(),
+        variant: BTreeMap::new(),
+    };
+
+    let example = find_model_example(&problem).expect("MultiprocessorScheduling example exists");
+    assert_eq!(example.problem, "MultiprocessorScheduling");
+    assert_eq!(example.variant, problem.variant);
+    assert!(example.instance.is_object());
+    assert!(
+        !example.optimal.is_empty(),
+        "canonical example should include satisfying assignments"
+    );
+}
+
 #[test]
 fn test_find_model_example_strong_connectivity_augmentation() {
     let problem = ProblemRef {
diff --git a/src/unit_tests/models/misc/multiprocessor_scheduling.rs b/src/unit_tests/models/misc/multiprocessor_scheduling.rs
new file mode 100644
index 000000000..13f63158d
--- /dev/null
+++ b/src/unit_tests/models/misc/multiprocessor_scheduling.rs
@@ -0,0 +1,147 @@
+use super::*;
+use crate::solvers::{BruteForce, Solver};
+use crate::traits::Problem;
+
+#[test]
+fn test_multiprocessor_scheduling_basic() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+    assert_eq!(problem.num_tasks(), 5);
+    assert_eq!(problem.total_length(), 20);
+    assert_eq!(problem.lengths(), &[4, 5, 3, 2, 6]);
+    assert_eq!(problem.num_processors(), 2);
+    assert_eq!(problem.deadline(), 10);
+    assert_eq!(problem.total_length(), 20);
+    assert_eq!(problem.dims(), vec![2; 5]);
+    assert_eq!(
+        <MultiprocessorScheduling as Problem>::NAME,
+        "MultiprocessorScheduling"
+    );
+    assert_eq!(<MultiprocessorScheduling as Problem>::variant(), vec![]);
+}
+
+#[test]
+fn test_multiprocessor_scheduling_feasible() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+    // Processor 0: tasks 0,4 => 4+6=10, Processor 1: tasks 1,2,3 => 5+3+2=10
+    assert!(problem.evaluate(&[0, 1, 1, 1, 0]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_infeasible() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+    // Processor 0: tasks 0,1,2,3,4 => 4+5+3+2+6=20 > 10
+    assert!(!problem.evaluate(&[0, 0, 0, 0, 0]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_infeasible_tight() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+    // Processor 0: tasks 0,1,4 => 4+5+6=15 > 10
+    assert!(!problem.evaluate(&[0, 0, 1, 1, 0]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_wrong_config_length() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3], 2, 10);
+    assert!(!problem.evaluate(&[0, 1]));
+    assert!(!problem.evaluate(&[0, 1, 0, 1]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_invalid_processor_index() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3], 2, 10);
+    // Processor index 2 is out of range for 2 processors
+    assert!(!problem.evaluate(&[0, 2, 0]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_empty_instance() {
+    let problem = MultiprocessorScheduling::new(vec![], 2, 10);
+    assert_eq!(problem.num_tasks(), 0);
+    assert_eq!(problem.dims(), Vec::<usize>::new());
+    // Empty assignment is always feasible
+    assert!(problem.evaluate(&[]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_single_task() {
+    let problem = MultiprocessorScheduling::new(vec![5], 2, 5);
+    assert!(problem.evaluate(&[0]));
+    assert!(problem.evaluate(&[1]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_single_task_exceeds_deadline() {
+    let problem = MultiprocessorScheduling::new(vec![11], 2, 10);
+    assert!(!problem.evaluate(&[0]));
+    assert!(!problem.evaluate(&[1]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_three_processors() {
+    let problem = MultiprocessorScheduling::new(vec![3, 3, 3], 3, 3);
+    assert_eq!(problem.dims(), vec![3; 3]);
+    // One task per processor
+    assert!(problem.evaluate(&[0, 1, 2]));
+    // Two tasks on one processor exceeds deadline
+    assert!(!problem.evaluate(&[0, 0, 1]));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_brute_force() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+    let solver = BruteForce::new();
+    let solution = solver.find_satisfying(&problem);
+    assert!(solution.is_some());
+    let config = solution.unwrap();
+    assert!(problem.evaluate(&config));
+}
+
+#[test]
+fn test_multiprocessor_scheduling_brute_force_infeasible() {
+    // Total length = 20, with 2 processors and deadline 9, impossible
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 9);
+    let solver = BruteForce::new();
+    let solution = solver.find_satisfying(&problem);
+    assert!(solution.is_none());
+}
+
+#[test]
+fn test_multiprocessor_scheduling_serialization() {
+    let problem = MultiprocessorScheduling::new(vec![4, 5, 3, 2, 6], 2, 10);
+    let json = serde_json::to_value(&problem).unwrap();
+    let restored: MultiprocessorScheduling = serde_json::from_value(json).unwrap();
+    assert_eq!(restored.lengths(), problem.lengths());
+    assert_eq!(restored.num_processors(), problem.num_processors());
+    assert_eq!(restored.deadline(), problem.deadline());
+}
+
+#[test]
+fn test_multiprocessor_scheduling_deserialization_rejects_zero_processors() {
+    let err = serde_json::from_value::<MultiprocessorScheduling>(serde_json::json!({
+        "lengths": [1, 2],
+        "num_processors": 0,
+        "deadline": 5
+    }))
+    .unwrap_err();
+    assert!(
+        err.to_string().contains("expected positive integer, got 0"),
+        "unexpected error: {err}"
+    );
+}
+
+#[test]
+#[should_panic(expected = "num_processors must be positive")]
+fn test_multiprocessor_scheduling_zero_processors() {
+    MultiprocessorScheduling::new(vec![1, 2], 0, 5);
+}
+
+#[test]
+fn test_multiprocessor_scheduling_deadline_zero() {
+    // Only feasible if all lengths are 0
+    let problem = MultiprocessorScheduling::new(vec![0, 0], 2, 0);
+    assert!(problem.evaluate(&[0, 1]));
+
+    let problem2 = MultiprocessorScheduling::new(vec![1, 0], 2, 0);
+    assert!(!problem2.evaluate(&[0, 1]));
+}