Сравнение на методи

	Генетичен алгоритъм	Tabu Search
Област	Оптимизация	Оптимизация
Семейство	Process / pipeline	Process / pipeline
Година на възникване	1975	1989
Създател	John Henry Holland	Fred Glover
Тип	Population-based metaheuristic	Local-search metaheuristic
Основополагащ източник	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.	Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206.
Други названия	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon	Tabu Araması (Tabu Search), TS, tabu metaheuristic
Свързани	5	4
Резюме	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.	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.