השוואת שיטות

	אופטימיזציית נחיל חלקיקים דטרמיניסטית	אלגוריתם גנטי
תחום	סימולציה	אופטימיזציה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1995 (PSO); deterministic formulation circa 2002	1975
הוגה השיטה	Kennedy, J., Eberhart, R. (PSO); deterministic variant formalized in convergence analysis literature	John Henry Holland
סוג	Swarm intelligence metaheuristic — deterministic variant	Population-based metaheuristic
מקור מכונן	Kennedy, J., Eberhart, R. (1995). Particle swarm optimization. Proceedings of ICNN'95 — International Conference on Neural Networks, vol. 4, pp. 1942–1948. IEEE.	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
כינויים	DPSO, Deterministic PSO, PSO without stochastic components, Fully Deterministic PSO	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
קשורות	6	5
תקציר	Deterministic 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.	A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.