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| Giải thuật luyện kim mô phỏng mạnh mẽ× | Tối ưu hóa Đa Mục tiêu Mạnh mẽ× | |
|---|---|---|
| Lĩnh vực | Mô phỏng | Mô phỏng |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1983 (SA); robust variant emerged 1990s–2000s | 2006 |
| Người khởi xướng≠ | Kirkpatrick, Gelatt & Vecchi (SA basis); robust formulation developed across the operations research community | Deb, K. & Gupta, H. |
| Loại≠ | Metaheuristic with robustness evaluation | Optimization framework |
| Công trình gốc≠ | Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671-680. DOI ↗ | Deb, K., & Gupta, H. (2006). Introducing robustness in multi-objective optimization. Evolutionary Computation, 14(4), 463–494. DOI ↗ |
| Tên gọi khác | RSA, Robust SA, Uncertainty-robust simulated annealing, Worst-case simulated annealing | RMOO, Robust MOO, Robust Pareto Optimization, Uncertainty-Robust Multi-Objective Optimization |
| Liên quan≠ | 5 | 4 |
| Tóm tắt≠ | Robust Simulated Annealing (RSA) adapts the classical simulated annealing metaheuristic to seek solutions that perform well not just under nominal conditions but across the full range of uncertain or adversarial parameter values. By embedding a robustness evaluation — worst-case, expected-case, or regret-based — into the SA acceptance step, RSA trades some nominal optimality for resilience, making it valuable when problem parameters are imprecisely known or subject to environmental variation. | Robust Multi-Objective Optimization (RMOO) is a framework for finding solutions that simultaneously optimize multiple conflicting objectives while remaining insensitive to perturbations in decision variables or problem parameters. Unlike classical MOO, RMOO explicitly incorporates uncertainty into the optimization loop, producing a robust Pareto front whose members perform well not only at the nominal design point but also across a neighbourhood of plausible operating conditions. |
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