方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 多目标离散事件仿真× | 离散事件仿真 (DES)× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s | 1960s (formalized); modern computational form from 1970s onward |
| 提出者≠ | Various (DES: Tocher 1963; multi-objective integration: 1990s–2000s OR literature) | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| 类型≠ | Simulation-optimization hybrid | Stochastic process simulation |
| 开创性文献≠ | 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 ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| 别名≠ | MO-DES, Multi-objective DES, Pareto-based discrete-event simulation, DES with multi-objective optimization | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| 相关≠ | 5 | 4 |
| 摘要≠ | 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. | Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time. |
| ScholarGate数据集 ↗ |
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