ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

決定版整数計画法×Branch and Bound(ブランチ・アンド・バウンド法)×
分野シミュレーション最適化
系統Process / pipelineProcess / pipeline
提唱年19581960
提唱者Ralph E. GomoryAilsa Land & Alison Doig
種類Exact combinatorial optimizationExact combinatorial optimization algorithm
原典Gomory, R. E. (1958). Outline of an algorithm for integer solutions to linear programs. Bulletin of the American Mathematical Society, 64(5), 275-278. DOI ↗Land, A. H., & Doig, A. G. (1960). An automatic method of solving discrete programming problems. Econometrica, 28(3), 497–520. DOI ↗
別名DIP, Integer Programming, IP, Integer Linear ProgrammingB&B, Land-Doig Algorithm, Implicit Enumeration, Dal ve Sınır
関連53
概要Deterministic Integer Programming (DIP) is a mathematical optimization approach that finds the best solution to problems where some or all decision variables must take integer values, given fully known (deterministic) objective and constraint data. It is the classical, non-stochastic form of integer programming, foundational to operations research and combinatorial optimization since the late 1950s.Branch and Bound is a systematic exact algorithm for combinatorial and integer optimization problems, introduced by Ailsa Land and Alison Doig in 1960. It organizes the search space as a tree of subproblems, uses relaxation-derived upper bounds to prune branches that cannot improve the best known solution, and guarantees finding a globally optimal integer solution. It is the backbone of modern mixed-integer programming solvers used in operations research, logistics, scheduling, and engineering design.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 1 出典
  3. PUBLISHED

検索へ Download slides

ScholarGate手法を比較: Deterministic Integer Programming · Branch and Bound. 2026-06-15に以下より取得 https://scholargate.app/ja/compare