方法证据记录
Multi-objective particle swarm optimization
Multi-Objective Particle Swarm Optimization (MOPSO) is a swarm-intelligence metaheuristic that extends the original Particle Swarm Optimization (PSO) to handle multiple conflicting objective functions simultaneously. It maintains an external Pareto archive and uses dominance-based selection to guide a population of candidate solutions toward the true Pareto front without requiring a priori preference information.
源记录
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Multi-Objective Particle Swarm Optimization (MOPSO)
分类方法记录 · process-pipeline / simulation
- Coello Coello, C. A., Pulido, G. T., & Lechuga, M. S. (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8(3), 256–279. · DOI 10.1109/TEVC.2004.826067
- Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks (ICNN), Perth, Australia, 4, 1942–1948. · DOI 10.1109/ICNN.1995.488968
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