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多目的アントコロニー最適化(MOACO)×Multi-Objective Simulated Annealing (MOSA)×
分野シミュレーションシミュレーション
系統Process / pipelineProcess / pipeline
提唱年19991992–1998
提唱者Gambardella, Taillard & Agazzi; Dorigo & StützleSerafini, P.; Czyzak, P. and Jaszkiewicz, A.
種類Population-based metaheuristicMetaheuristic / Pareto-based optimizer
原典Gambardella, L. M., Taillard, E., & Agazzi, G. (1999). MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In D. Corne, M. Dorigo, & F. Glover (Eds.), New Ideas in Optimization (pp. 63–76). McGraw-Hill. link ↗Czyzak, P., Jaszkiewicz, A. (1998). Pareto simulated annealing — a metaheuristic technique for multiple-objective combinatorial optimization. Journal of Multi-Criteria Decision Analysis, 7(1), 34–47. DOI ↗
別名MOACO, Multi-Objective ACO, Pareto Ant Colony Optimization, Multi-objective ACOMOSA, Multi-Criteria Simulated Annealing, Pareto Simulated Annealing, PSA
関連45
概要Multi-Objective Ant Colony Optimization (MOACO) is a swarm-intelligence metaheuristic that extends the classic Ant Colony Optimization framework to simultaneously optimize two or more conflicting objectives. Artificial ants construct candidate solutions guided by pheromone trails and heuristic information, progressively building an archive of Pareto-optimal solutions rather than converging to a single best answer.Multi-Objective Simulated Annealing (MOSA) extends the classical simulated annealing metaheuristic to problems with two or more conflicting objective functions. Instead of converging to a single optimum, MOSA explores the solution space stochastically and maintains an archive of non-dominated (Pareto-optimal) solutions, offering decision-makers a diverse trade-off front rather than one prescribed answer.
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ScholarGate手法を比較: Multi-objective ant colony optimization · Multi-objective simulated annealing. 2026-06-17に以下より取得 https://scholargate.app/ja/compare