Paper Info
Title
A modified PSO with a dynamically varying population and its application to the multi-objective optimal design of alloy steels
Abstract
In this paper, a new mechanism for dynamically varying the population size is proposed based on a previously modified PSO algorithm (nPSO). This new algorithm is extended to the multi-objective optimisation case by applying the Random Weighted Aggregation (RWA) technique and by maintaining an archive for preserving the suitable Pareto-optimal solutions. Both the single objective and multi-objective optimisation algorithms were tested using well-known benchmark problems. The results show that the proposed algorithms outperform some of the other salient Evolutionary Algorithms (EAs). The proposed algorithms were further applied successfully to the optimal design problem of alloy steels, which aims at determining the optimal heat treatment regime and the required weight percentages for chemical composites to obtain the desired mechanical properties of steel hence minimising production costs and achieving the overarching aim of 'right-first-time production' of metals.
Year
DOI
Venue
2009
10.1109/CEC.2009.4983355
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
optimal heat treatment regime,pso algorithm,new mechanism,dynamically varying population,multi-objective optimisation algorithm,new algorithm,multi-objective optimisation case,proposed algorithm,minimising production cost,optimal design problem,right-first-time production,alloy steel,multi-objective optimal design,modified pso,optimization,multi objective optimization,optimal design,evolutionary algorithm,production,cost function,chemical composition,population size,steel industry,evolutionary algorithms,algorithm design and analysis,evolutionary computation,benchmark testing,heat treatment
Particle swarm optimization,Population,Mathematical optimization,Algorithm design,Evolutionary algorithm,Computer science,Alloy steel,Evolutionary computation,Optimal design,Benchmark (computing)
Conference
Citations 
PageRank 
References 
5
0.45
6
Authors
2
Name
Order
Citations
PageRank
Qian Zhang1384.41
Mahdi Mahfouf223533.17