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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
Submitted: February 02, 2013
Accepted: March 02, 2013
Published: December 25, 2013 |
Abstract:
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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.
Key words: Complex system, constrain, Genetic Algorithm (GA), Multi-Objective Optimization (MOO), Pareto set, ,
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Cite this Reference:
Okafor Ekene Gabriel, Sun Youchao and Uhuegho Osaretin Kole , . Multi-Objective Optimization of a Complex System using GPSIA+DS. Research Journal of Applied Sciences, Engineering and Technology, (24): 4621-4629.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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