方法证据记录
Multi-Objective Optimization
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Multi-Objective Optimization (MOO) — simultaneous optimization of two or more conflicting objective functions
分类方法记录 · process-pipeline / simulation
- Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. · ISBN 9780471873396
- Multi-objective optimization. Wikipedia. · URL
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