Unified Particle Swarm Optimization for Solving Constrained Engineering Optimization Problems

We investigate the performance of the recently proposed Unified Particle Swarm Optimization method on constrained engineering optimization problems. For this purpose, a penalty function approach is employed and the algorithm is modified to preserve feasibility of the encountered solutions. The algor...

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Bibliographic Details
Published inAdvances in Natural Computation pp. 582 - 591
Main Authors Parsopoulos, K. E., Vrahatis, M. N.
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Design Variable
Exact sciences and technology
Gear Train
Particle Swarm Optimization
Particle Swarm Optimization Method
Penalty Function
Penalty function
Optimization method
Problem solving
Feasibility
Swarm intelligence
Constrained optimization
Mathematical programming
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Summary:We investigate the performance of the recently proposed Unified Particle Swarm Optimization method on constrained engineering optimization problems. For this purpose, a penalty function approach is employed and the algorithm is modified to preserve feasibility of the encountered solutions. The algorithm is illustrated on four well–known engineering problems with promising results. Comparisons with the standard local and global variant of Particle Swarm Optimization are reported and discussed.
ISBN:9783540283201
354028320X
3540283234
9783540283232
ISSN:0302-9743
1611-3349
DOI:10.1007/11539902_71