Abstract
This paper presents a new multiobjective particle swarm optimization (MOPSO) technique to solve environmental/economic dispatch (EED) problem. The EED problem is a non-linear constrained multiobjective optimization problem. The Multi-objective Dynamic Multi-Swarm Particle Swarm Optimizer (DMS-MO-PSO) proposed employs novel pbest and lbest updating criteria which are more suitable for solving multi-objective problems. In this work, the standard IEEE 30-bus six-generator test system is used and simulation results showed that the proposed approach is efficient and confirms its potential to solve the multiobjective EED problem. © 2012 Springer-Verlag.
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Liang, J. J., Zhang, W. X., Qu, B. Y., & Chen, T. J. (2012). Multiobjective dynamic multi-swarm particle swarm optimization for environmental/economic dispatch problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7389 LNCS, pp. 657–664). https://doi.org/10.1007/978-3-642-31588-6_84
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