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| Tìm kiếm lân cận biến đổi (VNS)× | Thuật toán di truyền× | |
|---|---|---|
| Lĩnh vực | Tối ưu hóa | Tối ưu hóa |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1997 | 1975 |
| Người khởi xướng≠ | — | John Henry Holland |
| Loại≠ | Metaheuristic — neighborhood-based | Population-based metaheuristic |
| Công trình gốc≠ | Mladenović, N. & Hansen, P. (1997). Variable Neighborhood Search. Computers & Operations Research, 24(11), 1097–1100. DOI ↗ | Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗ |
| Tên gọi khác | VNS, Değişken Komşuluk Araması (VNS), variable neighbourhood search | GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon |
| Liên quan≠ | 4 | 5 |
| Tóm tắt≠ | Variable Neighborhood Search (VNS) is a metaheuristic optimization framework introduced by Mladenović and Hansen in 1997. It escapes local optima by systematically switching among a predefined set of neighborhood structures — first perturbing the current solution (shaking) to reach a different region of the search space, then applying a local search within that region, and finally accepting the new solution only if it improves the incumbent. The method is flexible enough to handle combinatorial problems (routing, scheduling, graph problems) as well as continuous optimization, making it one of the most widely used neighborhood-based metaheuristics in operations research. | 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. |
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