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	Przeszukiwanie tabu	Optymalizacja rojem cząstek (PSO)
Dziedzina	Optymalizacja	Optymalizacja
Rodzina	Process / pipeline	Process / pipeline
Rok powstania	1989	1995
Twórca	Fred Glover	—
Typ	Local-search metaheuristic	Population-based metaheuristic / swarm intelligence
Źródło pierwotne	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.
Inne nazwy	Tabu Araması (Tabu Search), TS, tabu metaheuristic	PSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO)
Pokrewne	4	6
Podsumowanie	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.