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。

タブーサーチ×Particle Swarm Optimization (PSO)×
分野最適化最適化
系統Process / pipelineProcess / pipeline
提唱年19891995
提唱者Fred Glover
種類Local-search metaheuristicPopulation-based metaheuristic / swarm intelligence
原典Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206. link ↗Kennedy, J. & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks (ICNN), 1942-1948. DOI ↗
別名Tabu Araması (Tabu Search), TS, tabu metaheuristicPSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO)
関連46
概要Tabu Search is a local-search metaheuristic introduced by Fred Glover in 1989 that uses a tabu list — a short-term memory of recently visited solutions — to prevent cycling and escape local optima. By explicitly forbidding moves that reverse recent decisions, the algorithm explores the search space more broadly and, through long-term memory structures such as aspiration criteria, aims to approach the global optimum even in large, complex combinatorial problems.Particle Swarm Optimization (PSO) is a population-based metaheuristic algorithm introduced by Kennedy and Eberhart in 1995, inspired by the collective movement of bird flocks and fish schools. Each candidate solution — called a particle — moves through the search space by updating its velocity and position based on its own best experience and the best experience of the entire swarm, enabling fast convergence across continuous optimization problems.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Tabu Search · Particle Swarm Optimization. 2026-06-18に以下より取得 https://scholargate.app/ja/compare