Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Стохастический поиск с запретами× | Генетический алгоритм× | |
|---|---|---|
| Область≠ | Имитационное моделирование | Оптимизация |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1990s | 1975 |
| Автор метода≠ | Glover, F. (base TS); stochastic extensions by various authors (1990s–2000s) | John Henry Holland |
| Тип≠ | Stochastic metaheuristic optimizer | Population-based metaheuristic |
| Основополагающий источник≠ | Glover, F. (1990). Tabu search: A tutorial. Interfaces, 20(4), 74-94. DOI ↗ | Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗ |
| Другие названия≠ | STS, Randomized Tabu Search, Probabilistic Tabu Search, Noisy Tabu Search | GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon |
| Связанные | 5 | 5 |
| Сводка≠ | Stochastic Tabu Search (STS) is an extension of classical Tabu Search that introduces randomness into the neighborhood exploration and move-selection phases. By combining tabu memory — which forbids recently visited solutions — with probabilistic acceptance or random candidate sampling, STS escapes local optima more effectively and explores rugged solution landscapes that deterministic TS may fail to traverse. | 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. |
| ScholarGateНабор данных ↗ |
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