DocumentCode :
226663
Title :
Using heterogeneous knowledge sharing strategies with dynamic vector-evaluated particle swarm optimisation
Author :
Helbig, Marde ; Engelbrecht, Andries P.
Author_Institution :
Dept. of Comput. Sci., Univ. of Pretoria, Pretoria, South Africa
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
1
Lastpage :
8
Abstract :
Dynamic multi-objective optimisation problems have more than one objective with at least one objective that changes over time. Previous studies indicated that different knowledge sharing strategies increase the performance of the dynamic vector evaluated particle swarm optimisation (DVEPSO) algorithm in different dynamic environments. Therefore, this paper investigates the performance of the DVEPSO algorithm using heterogeneous particle swarm optimisation (HPSO) algorithms, where each particle uses a different knowledge sharing strategy. The goal of this study is to determine whether the use of HPSOs will improve the performance of DVEPSO by incorporating particles with different knowledge sharing strategies in a single DVEPSO algorithm. The results indicate that using HPSOs improves the performance of DVEPSO for dynamic multi-objective optimisation problems with a complex Pareto-optimal set and that the performance of heterogeneous DVEPSO compares favourably with that of DVEPSO.
Keywords :
particle swarm optimisation; swarm intelligence; vectors; DVEPSO algorithm; HPSO algorithms; complex Pareto-optimal set; dynamic vector-evaluated particle swarm optimisation; heterogeneous DVEPSO; heterogeneous knowledge sharing strategies; heterogeneous particle swarm optimisation; Benchmark testing; Heuristic algorithms; Loss measurement; Optical fibers; Optimization; Particle swarm optimization; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Swarm Intelligence (SIS), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/SIS.2014.7011804
Filename :
7011804
Link To Document :
بازگشت