Summary
This chapter presents a synergistic combination of particle swarm optimization and evolutionary algorithm for optimization problems. The performance of the hybrid algorithm is bench-marked against conventional genetic algorithm and particle swarm optimization algorithm. Finally, the hybrid algorithm is illustrated as a multiobjective optimization algorithm using the Fonseca 2-objective function.
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Srinivasan, D., Seow, T.H. (2005). Particle Swarm Inspired Evolutionary Algorithm (PS-EA) for Multi-Criteria Optimization Problems. In: Abraham, A., Jain, L., Goldberg, R. (eds) Evolutionary Multiobjective Optimization. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/1-84628-137-7_7
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DOI: https://doi.org/10.1007/1-84628-137-7_7
Publisher Name: Springer, London
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