DocumentCode
1637789
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
fYear
2009
Firstpage
1255
Lastpage
1262
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/CEC.2009.4983089
Filename
4983089
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