Solving the Two-dimensional single stock size Cuting Stock Problem with SAT and MaxSAT

Dimensions overall score 4.0

• The SAT-based framework for 2D-CSSP expands item types by demand and uses sheet-assignment variables with non-overlap constraints activated only for copies assigned to the same sheet.method 90%
  Evidencepartial

  We present a SAT-based framework where item types are expanded by demand, each copy has a sheet-assignment variable and non-overlap constraints are activated only for copies assigned to the same sheet.

  Implicationpartial

  Directly stated in the abstract describing the core method

  Verificationpartial

  partial

• An infeasible-orientation elimination rule fixes rotation variables when only one orientation can fit the sheet.technical 90%
  Evidencepartial

  We also introduce an infeasible-orientation elimination rule that fixes rotation variables when only one orientation can fit the sheet.

  Implicationpartial

  Directly stated in the abstract as a specific technical contribution

  Verificationpartial

  partial

• For minimizing sheets, three SAT approaches are compared: non-incremental SAT with binary search, incremental SAT with clause reuse, and weighted partial MaxSAT.method 90%
  Evidencepartial

  For minimizing the number of sheets, we compare three approaches: non-incremental SAT with binary search, incremental SAT with clause reuse across iterations and weighted partial MaxSAT.

  Implicationpartial

  Directly stated in the abstract with clear enumeration of methods

  Verificationpartial

  partial

• On the Cui--Zhao benchmark suite, the best SAT configurations certify two to three times more instances as provably optimal than OR-Tools, CPLEX and Gurobi.result 85%
  Evidencepartial

  On the Cui--Zhao benchmark suite, our best SAT configurations certify two to three times more instances as provably optimal and achieve lower optimality gaps than OR-Tools, CPLEX and Gurobi.

  Implicationpartial

  Directly stated in abstract with comparative performance metric

  Verificationpartial

  partial

• The relative ranking among SAT approaches depends on rotation: incremental SAT is strongest without rotation, while non-incremental SAT is more effective when rotation increases formula size.result 85%
  Evidencepartial

  The relative ranking among SAT approaches depends on rotation: incremental SAT is strongest without rotation, while non-incremental SAT is more effective when rotation increases formula size.

  Implicationpartial

  Directly stated in abstract as a key finding about method performance

  Verificationpartial

  partial

• The 2D-CSSP generalizes bin packing by requiring multiple copies of each item type, causing a strong combinatorial blow-up.technical 80%
  Evidencepartial

  The Two-Dimensional Single Stock Size Cutting Stock Problem (2D-CSSP) generalizes bin packing by requiring multiple copies of each item type, which causes a strong combinatorial blow-up.

  Implicationpartial

  Directly stated in abstract as problem characterization

  Verificationpartial

  partial

• The SAT-based approaches achieve lower optimality gaps than OR-Tools, CPLEX and Gurobi on the benchmark suite.result 85%
  Evidencepartial

  On the Cui--Zhao benchmark suite, our best SAT configurations certify two to three times more instances as provably optimal and achieve lower optimality gaps than OR-Tools, CPLEX and Gurobi.

  Implicationpartial

  Directly stated in abstract as comparative performance result

  Verificationpartial

  partial

Competitive landscape

A SAT-based framework for optimizing the 2D cutting stock problem, outperforming existing solvers on benchmark instances.