方法对比
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| 多目标排队仿真× | 多目标离散事件仿真× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份 | 1990s–2000s | 1990s–2000s |
| 提出者≠ | Operations research community (Banks, Deb, and related authors) | Various (DES: Tocher 1963; multi-objective integration: 1990s–2000s OR literature) |
| 类型≠ | Simulation-based multi-objective optimization | Simulation-optimization hybrid |
| 开创性文献≠ | Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Pearson Prentice Hall. ISBN: 9780136062127 | 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 ↗ |
| 别名 | MOQS, Multi-criteria Queueing Simulation, Multi-objective Queue Optimization, Pareto Queueing Simulation | MO-DES, Multi-objective DES, Pareto-based discrete-event simulation, DES with multi-objective optimization |
| 相关≠ | 4 | 5 |
| 摘要≠ | Multi-objective queueing simulation combines discrete-event queueing models with multi-objective optimization to simultaneously evaluate and optimize conflicting performance metrics — such as average wait time, server utilization, throughput, and service cost — across a simulated queuing system. It produces a Pareto front of non-dominated solutions rather than a single optimal point, enabling decision-makers to understand trade-offs explicitly. | 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. |
| ScholarGate数据集 ↗ |
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