Сравнение методов

	Tabu Search	Оптимизация роем частиц (PSO)
Область	Оптимизация	Оптимизация
Семейство	Process / pipeline	Process / pipeline
Год появления	1989	1995
Автор метода	Fred Glover	—
Тип	Local-search metaheuristic	Population-based metaheuristic / swarm intelligence
Основополагающий источник	Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206.	Kennedy, J. & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks (ICNN), 1942-1948.
Другие названия	Tabu Araması (Tabu Search), TS, tabu metaheuristic	PSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO)
Связанные	4	6
Сводка	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.