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| 多目标线性规划 (MOLP)× | 多目标优化× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1955–1986 | 1896 (concept); 1989–2002 (evolutionary algorithms era) |
| 提出者≠ | Steuer, R. E.; Charnes, A.; Cooper, W. W. | Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al. |
| 类型≠ | Mathematical optimization / vector optimization | Optimization framework |
| 开创性文献≠ | Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468 | Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396 |
| 别名 | MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization | MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization |
| 相关 | 3 | 3 |
| 摘要≠ | Multi-Objective Linear Programming (MOLP) extends classical linear programming to handle several conflicting linear objective functions simultaneously over a feasible region defined by linear constraints. Instead of a single optimal solution, MOLP produces a Pareto-efficient frontier from which a decision-maker selects a preferred trade-off. It is foundational to operations research and management science for resource allocation, planning, and design problems with competing goals. | 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. |
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