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Deterministyczna optymalizacja rojem cząstek×Wyżarzanie symulowane×
DziedzinaSymulacjaOptymalizacja
RodzinaProcess / pipelineProcess / pipeline
Rok powstania1995 (PSO); deterministic formulation circa 20021983
TwórcaKennedy, J., Eberhart, R. (PSO); deterministic variant formalized in convergence analysis literature
TypSwarm intelligence metaheuristic — deterministic variantProbabilistic metaheuristic / local search
Źródło pierwotneKennedy, J., Eberhart, R. (1995). Particle swarm optimization. Proceedings of ICNN'95 — International Conference on Neural Networks, vol. 4, pp. 1942–1948. IEEE. DOI ↗Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗
Inne nazwyDPSO, Deterministic PSO, PSO without stochastic components, Fully Deterministic PSOBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local search
Pokrewne65
PodsumowanieDeterministic Particle Swarm Optimization (DPSO) removes the stochastic random coefficients from classical PSO, replacing them with fixed cognitive and social acceleration parameters. Particles move through the search space following fully predictable trajectories, enabling reproducible convergence analysis and guaranteed termination behavior in continuous and combinatorial optimization problems.Simulated annealing is a probabilistic local-search metaheuristic introduced by Kirkpatrick, Gelatt, and Vecchi in 1983. It models the physical annealing process in metallurgy — where a material is heated and then slowly cooled to reach a low-energy crystalline state — and uses this analogy to escape local optima in combinatorial and continuous optimization problems.
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ScholarGatePorównaj metody: Deterministic Particle Swarm Optimization · Simulated Annealing. Pobrano 2026-06-18 z https://scholargate.app/pl/compare