方法证据记录
Multi-objective genetic algorithm
A Multi-Objective Genetic Algorithm (MOGA) is an evolutionary computation method that evolves a population of candidate solutions toward a Pareto-optimal front, simultaneously optimizing two or more conflicting objective functions. It avoids collapsing trade-offs into a single score, instead producing a set of non-dominated solutions for the decision-maker to choose among.
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 Genetic Algorithm (MOGA)
分类方法记录 · process-pipeline / simulation
- Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley. · ISBN 9780201157673
- Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. · DOI 10.1109/4235.996017
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