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2013 (Vol. 6, Issue: 24)
Article Information:

Multi-Objective Optimization of a Complex System using GPSIA+DS

Okafor Ekene Gabriel, Sun Youchao and Uhuegho Osaretin Kole
Corresponding Author:  Okafor Ekene Gabriel 

Key words:  Complex system, constrain, Genetic Algorithm (GA), Multi-Objective Optimization (MOO), Pareto set, ,
Vol. 6 , (24): 4621-4629
Submitted Accepted Published
February 02, 2013 March 02, 2013 December 25, 2013
Abstract:

n this study, an efficient biologically inspired constrained multi-objective optimization algorithm called Genetic Pareto Set Identification Algorithm plus Different Sex (GPSIA+DS) was developed. A complex system comprising of mixed configuration, k-out-of-n and redundant subsystem was used to validate GPSIA+DS in comparison with Genetic Pareto Set Identification Algorithm (GPSIA) and Fast Non–Dominated Sorting Genetic Algorithm plus Constrain Domination (NSGA-II+CD). The optimization strategy based on Genetic Pareto Set Identification Algorithm (GPSIA) only considered feasible solutions. That is, solutions, which satisfies all constraints conditions. Infeasible solutions could facilitate faster convergence to the true Pareto front. GPSIA+DS, which considers feasible and infeasible solutions in it optimization strategy was shown to outperform GPSIA and NSGA-II for the test problem considered.
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  Cite this Reference:
Okafor Ekene Gabriel, Sun Youchao and Uhuegho Osaretin Kole , 2013. Multi-Objective Optimization of a Complex System using GPSIA+DS.  Research Journal of Applied Sciences, Engineering and Technology, 6(24): 4621-4629.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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