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遺伝的アルゴリズム×ゴールプログラミング×
分野最適化意思決定
系統Process / pipelineMCDM
提唱年19751955
提唱者John Henry HollandCharnes, A., Cooper, W. W.
種類Population-based metaheuristicMulti-objective optimisation — weighted/lexicographic goal deviation minimisation
原典Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science DOI ↗
別名GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
関連58
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.GOAL-PROGRAMMING (Goal Programming — Minimise deviations from multiple aspiration levels) is a ranking multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W. in 1955. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGate手法を比較: Genetic Algorithm · GOAL-PROGRAMMING. 2026-06-15に以下より取得 https://scholargate.app/ja/compare