مقایسهٔ روشها
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| برنامهریزی هدف قوی× | بهینهسازی چندهدفه استوار× | |
|---|---|---|
| حوزه | شبیهسازی | شبیهسازی |
| خانواده | Process / pipeline | Process / pipeline |
| سال پیدایش≠ | 1961 (GP); 1990s (robust extension) | 2006 |
| پدیدآور≠ | Charnes, A. & Cooper, W. W. (goal programming); Mulvey, J. M. et al. (robust optimization framework) | Deb, K. & Gupta, H. |
| نوع≠ | Mathematical programming under uncertainty | Optimization framework |
| منبع بنیادین≠ | Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 9780471155041 | Deb, K., & Gupta, H. (2006). Introducing robustness in multi-objective optimization. Evolutionary Computation, 14(4), 463–494. DOI ↗ |
| نامهای دیگر | RGP, Goal Programming under Uncertainty, Robust GP, Uncertainty-Aware Goal Programming | RMOO, Robust MOO, Robust Pareto Optimization, Uncertainty-Robust Multi-Objective Optimization |
| مرتبط≠ | 5 | 4 |
| خلاصه≠ | Robust Goal Programming (RGP) extends classical goal programming to handle uncertain or ambiguous model parameters. Instead of minimizing deviations from crisp targets, it seeks solutions that remain feasible and near-optimal across a range of plausible scenarios or uncertain data realizations. RGP is particularly valuable in planning problems where goals are aspirational and input data carries inherent variability or estimation error. | 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. |
| ScholarGateمجموعهداده ↗ |
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