Process / pipelineSimulation / optimization
随机多目标优化 — 在不确定性下优化多个冲突目标
随机多目标优化 (Stochastic Multi-Objective Optimization, SMOO) 是一类方法，用于在参数、成本或约束不确定或随机时，同时优化两个或多个相互冲突的目标。它不产生单一的最优解，而是生成一个帕累托前沿 (Pareto front) 的非支配解集，每个解代表在模型化不确定性下目标之间的一种不同权衡。
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来源
- Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396
- Caramia, M., Dell'Olmo, P. (2008). Multi-Objective Management in Freight Logistics. Springer, London. DOI: 10.1007/978-1-84800-382-8 ↗
如何引用本页
ScholarGate. (2026, June 3). Stochastic Multi-Objective Optimization — Multi-criteria optimization under uncertainty with probabilistic objectives or constraints. ScholarGate. https://scholargate.app/zh/simulation/stochastic-multi-objective-optimization
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