Evaluated Preference Genetic Algorithm and its Engineering Applications

This paper proposes a novel multiobjective genetic algorithm (MOGA), Evaluated Preference Genetic Algorithm (EPGA), for efficiently solving engineering multiobjective optimization problems. EPGA utilizes a preferred objective vector to perform a fast multiobjective ranking schema within a low comput...

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Published in:Key engineering materials 2011-01, Vol.467-469 (SUPPL.3), p.2129-2136
Main Authors: Liu, Tung Kuan, Wu, Wen Ping, Ho, Min Rong, Chen, Chiu Hung, Chang, Hsin Yuan
Format: Article
Language:English
Subjects:
Algorithms
Genetic algorithms
Genetics
Mathematical analysis
Mathematical models
Optimization
Pareto optimality
Vectors (mathematics)
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Wu, Wen Ping
Ho, Min Rong
Chen, Chiu Hung
Chang, Hsin Yuan
description This paper proposes a novel multiobjective genetic algorithm (MOGA), Evaluated Preference Genetic Algorithm (EPGA), for efficiently solving engineering multiobjective optimization problems. EPGA utilizes a preferred objective vector to perform a fast multiobjective ranking schema within a low computation complexity O(MNlogN) where N is the size of genetic population and M is the number of objectives. For verifying the proposed algorithms, this paper studies two engineering problems in which multiple mutual-conflicted objectives should be considered. According to the experimental results, the proposed EPGA can efficiently explore the Pareto front and provide very good solution capabilities for the engineering optimization problems.
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subjects Algorithms
Genetic algorithms
Genetics
Mathematical analysis
Mathematical models
Optimization
Pareto optimality
Vectors (mathematics)
title Evaluated Preference Genetic Algorithm and its Engineering Applications
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