مقایسهٔ روشها
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| شبیهسازی رویداد-گسسته چندهدفه× | بهینهسازی چندهدفه× | |
|---|---|---|
| حوزه | شبیهسازی | شبیهسازی |
| خانواده | Process / pipeline | Process / pipeline |
| سال پیدایش≠ | 1990s–2000s | 1896 (concept); 1989–2002 (evolutionary algorithms era) |
| پدیدآور≠ | Various (DES: Tocher 1963; multi-objective integration: 1990s–2000s OR literature) | Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al. |
| نوع≠ | Simulation-optimization hybrid | Optimization framework |
| منبع بنیادین≠ | Kleijnen, J. P. C., & Gaury, E. (2003). Short-term robustness of production management systems: A case study. European Journal of Operational Research, 148(2), 452–465. DOI ↗ | Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396 |
| نامهای دیگر | MO-DES, Multi-objective DES, Pareto-based discrete-event simulation, DES with multi-objective optimization | MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization |
| مرتبط≠ | 5 | 3 |
| خلاصه≠ | Multi-Objective Discrete-Event Simulation (MO-DES) couples a discrete-event simulation engine with multi-objective optimization to explore trade-offs among two or more conflicting performance measures — such as throughput, cost, and waiting time — across stochastic, time-ordered process models. It is widely applied in manufacturing, logistics, healthcare, and service system design. | Multi-Objective Optimization (MOO) is a mathematical and computational framework for finding solutions that simultaneously optimize two or more conflicting objective functions. Rather than collapsing all goals into a single scalar, MOO produces a set of trade-off solutions — the Pareto front — from which a decision-maker selects according to preference. It is widely used in engineering design, operations research, logistics, economics, and policy analysis. |
| ScholarGateمجموعهداده ↗ |
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