AWhat changed
Benders partitions a mixed-variable optimization problem into a master problem and a linear subproblem, generating only the dual constraints needed to identify an optimum or detect infeasibility or unboundedness, under explicit solution and compactness assumptions.
Scientific scope
Benders partitions a mixed-variable optimization problem into a master problem and a linear subproblem, generating only the dual constraints needed to identify an optimum or detect infeasibility or unboundedness, under explicit solution and compactness assumptions. The partitioned subproblem is linear; the remaining master problem may still be difficult. The computational argument assumes the stated boundedness/continuity and correctly solved master/subproblems. Finite polyhedral generators support feasibility-ray and optimality-point cuts, not polynomial runtime for every mixed problem. A big-M variant requires a sufficiently large/adapted value or a separate phase. Reported test cases are not an independently reproduced performance study.
Evidence
Source-linked, scoped account of the original work. The published scope states the scientific assumptions and remaining verification limits. WRS has not independently certified the full proof, experimental result or system benchmark.
Contributors
- J. F. Benders · SCIENCE: Original source-listed scientific author of this scoped work; byline does not determine effort fractions.
- J. F. Benders, Partitioning procedures for solving mixed-variables programming problems; exact 1962 original
- Publisher-deposited identity for the exact 1962 Benders partitioning paper
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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