השוואת שיטות

	אלגוריתם אופטימיזציית לווייתנים (WOA)	אלגוריתם גנטי
תחום	אופטימיזציה	אופטימיזציה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	2016	1975
הוגה השיטה	Seyedali Mirjalili & Andrew Lewis	John Henry Holland
סוג	Swarm-based metaheuristic	Population-based metaheuristic
מקור מכונן	Mirjalili, S. & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67.	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
כינויים	WOA, Balina Optimizasyon Algoritması (WOA), bubble-net attacking method	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
קשורות	5	5
תקציר	The Whale Optimization Algorithm (WOA) is a swarm-based metaheuristic introduced by Mirjalili and Lewis in 2016. It models the bubble-net hunting strategy of humpback whales, in which a group of whales spirals around prey while gradually tightening the encirclement. The algorithm balances global exploration and local exploitation through a small set of parameters and has become widely used in continuous engineering optimisation 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.