Process / pipelineSimulation / optimization
多目标优化 — 同时优化冲突目标
多目标优化（Multi-Objective Optimization, MOO）是一个数学和计算框架，用于寻找能够同时优化两个或多个冲突目标函数的解。MOO不将所有目标合并为一个标量，而是产生一组权衡解——帕累托前沿（Pareto front）——决策者从中根据偏好进行选择。它广泛应用于工程设计、运筹学、物流学、经济学和政策分析。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
+19 more
来源
- Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396
- Multi-objective optimization. Wikipedia. link ↗
如何引用本页
ScholarGate. (2026, June 3). Multi-Objective Optimization (MOO) — simultaneous optimization of two or more conflicting objective functions. ScholarGate. https://scholargate.app/zh/simulation/multi-objective-optimization
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
Compare side by side →