Abstract
Hybridization is one of the important research area in evolutionary multiobjective optimization (EMO).It is a method that incorporate good merits of multiple techniques aim at to enhance the search ability of EMO algorithm. In this chapter, we combine two well-known search algorithms, DE and PSO, and developed algorithm known as MOEA/D-DE+PSO. We experimentally studied its performance on two types of continuous multi-objective optimization problems and found better improvement.
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Mashwani, W.K. (2011). MOEA/D with DE and PSO: MOEA/D-DE+PSO. In: Bramer, M., Petridis, M., Nolle, L. (eds) Research and Development in Intelligent Systems XXVIII. SGAI 2011. Springer, London. https://doi.org/10.1007/978-1-4471-2318-7_16
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DOI: https://doi.org/10.1007/978-1-4471-2318-7_16
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