Title :
Analyses of guide update approaches for vector evaluated particle swarm optimisation on dynamic multi-objective optimisation problems
Author :
Helbig, Mardé ; Engelbrecht, Andries P.
Author_Institution :
CSIR: Meraka Inst., Pretoria, South Africa
Abstract :
The vector evaluated particle swarm optimisation (VEPSO) algorithm is a multi-swarm variation of particle swarm optimisation (PSO) used to solve static multi-objective optimisation problems (SMOOPs). Recently, VEPSO was extended to the dynamic VEPSO (DVEPSO) algorithm to solve dynamic multi-objective optimisation problems (DMOOPs) that have at least one objective that changes over time. The search process of DVEPSO is driven through local and global guides that can be updated in various ways. This paper investigates the influence of various guide update approaches on the performance of DVEPSO. DVEPSO is also compared against a competitive-cooperative evolutionary algorithm. The results indicate that DVEPSO performs well in fast changing environments, but struggles to converge to discontinuous Pareto-optimal fronts (POFs).
Keywords :
Pareto optimisation; dynamic programming; evolutionary computation; particle swarm optimisation; search problems; SMOOP; competitive-cooperative evolutionary algorithm; discontinuous Pareto-optimal front; dynamic VEPSO algorithm; dynamic multiobjective optimisation problem; global guide; guide update approach; local guide; search process; static multiobjective optimisation problem; vector evaluated particle swarm optimisation; Benchmark testing; Heuristic algorithms; Optical fibers; Optimization; Particle swarm optimization; Topology; Vectors;
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
DOI :
10.1109/CEC.2012.6252882
