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| Robust Tabu Search× | 강건한 입자 군집 최적화× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1989 (TS); robust variant ~2000s | 2000s |
| 창시자≠ | Glover, F. (Tabu Search); robustness extensions by various authors | Kennedy, J. & Eberhart, R. C. (PSO); robustness extensions by multiple authors, 2000s |
| 유형≠ | Metaheuristic with robustness mechanism | Metaheuristic — robust swarm-based optimizer |
| 원전≠ | Glover, F. (1989). Tabu search — Part I. ORSA Journal on Computing, 1(3), 190–206. DOI ↗ | Kennedy, J., Eberhart, R. C., & Shi, Y. (2001). Swarm Intelligence. Morgan Kaufmann Publishers. ISBN: 9781558605954 |
| 별칭 | RTS, Robust TS, Uncertainty-aware Tabu Search, Tabu Search under Uncertainty | Robust PSO, RPSO, Uncertainty-robust PSO, PSO with robustness |
| 관련 | 6 | 6 |
| 요약≠ | Robust Tabu Search (RTS) extends the classical Tabu Search metaheuristic by evaluating candidate solutions not only on their nominal objective value but also on their performance under uncertainty. Instead of seeking the best solution for a single scenario, RTS seeks solutions that perform well across a range of scenarios or realizations, trading peak optimality for reliability. | Robust Particle Swarm Optimization (Robust PSO) extends the classical PSO metaheuristic to explicitly account for uncertainty in the objective function, constraints, or decision variables. Rather than optimizing a single nominal objective, each candidate solution is evaluated over a set of uncertainty scenarios, and fitness is judged by a robustness criterion such as worst-case performance or expected value, yielding solutions that remain near-optimal even when conditions deviate from nominal assumptions. |
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