MEMPSODE: comparing particle swarm optimization and differential evolution within a hybrid memetic global optimization framework

Authors:
Costas Voglis;Grigoris S. Piperagkas;Konstantinos E. Parsopoulos;Dimitris G. Papageorgiou;Isaac E. Lagaris
Affiliations:
University of Ioannina, Ioannina, Greece;University of Ioannina, Ioannina, Greece;University of Ioannina, Ioannina, Greece;University of Ioannina, Ioannina, Greece;University of Ioannina, Ioannina, Greece
Venue:
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Year:
2012

Citing 6
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Abstract

MEMPSODE is a recently published optimization software that implements memetic Particle Swarm Optimization and Differential Evolution approaches. It combines previously proposed variants of the two algorithms, with the Merlin optimization environment, which includes a variety of established local search methods for continuous optimization. The present study aims at comparing the performance of the memetic variants produced by the two metaheuristics within the framework of MEMPSODE. The algorithms are assessed on the noiseless testbed of the Black-Box Optimization Benchmarking 2012 workshop, providing useful insight regarding their relative efficiency and effectiveness.