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遺伝的アルゴリズム×混合整数計画法×
分野最適化シミュレーション
系統Process / pipelineProcess / pipeline
提唱年19751958–1960
提唱者John Henry HollandRalph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)
種類Population-based metaheuristicMathematical optimization
原典Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432
別名GA, evolutionary algorithm, Genetik Algoritma — Evrimsel OptimizasyonMIP, Mixed-Integer Linear Programming, MILP, Integer Programming
関連56
概要A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.Mixed-Integer Programming (MIP) is a mathematical optimization framework in which some decision variables must take integer values while others may be continuous. It generalizes linear programming and is widely used in operations research, logistics, scheduling, resource allocation, and engineering design, where indivisibility constraints — such as yes/no decisions or whole-unit quantities — arise naturally.
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ScholarGate手法を比較: Genetic Algorithm · Mixed-Integer Programming. 2026-06-15に以下より取得 https://scholargate.app/ja/compare