Title :
Hybridizing PSO and DE for improved vector evaluated multi-objective optimization
Author :
Grobler, Jacomine ; Engelbrecht, Andries P.
Author_Institution :
Dept. of Ind. & Syst. Eng., Univ. of Pretoria, Pretoria
Abstract :
This paper introduces a new vector evaluated multi-objective optimization algorithm. The vector evaluated differential evolution particle swarm optimization (VEDEPSO) algorithm is a hybridization of the classical vector evaluated particle swarm optimization (VEPSO) and vector evaluated differential evolution (VEDE) algorithms of Parsopoulos et. al. Comparisons of VEDEPSO with respect to VEPSO and VEDE on a well known multi-objective benchmark problem set indicated that significant performance improvements can be attributed to the VEDEPSO algorithm.
Keywords :
evolutionary computation; particle swarm optimisation; PSO; differential evolution; particle swarm optimization; vector evaluated multiobjective optimization; Algorithm design and analysis; Computer industry; Computer science; Costs; Decision making; Functional analysis; Optimization methods; Particle swarm optimization; Performance analysis; Systems engineering and theory;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983089
