Paper Title:
Evaluated Preference Genetic Algorithm and its Engineering Applications
  Abstract

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.

  Info
Periodical
Key Engineering Materials (Volumes 467-469)
Edited by
Dehuai Zeng
Pages
2129-2136
DOI
10.4028/www.scientific.net/KEM.467-469.2129
Citation
T. K. Liu, H. Y. Chang, W. P. Wu, C. H. Chen, M. R. Ho, "Evaluated Preference Genetic Algorithm and its Engineering Applications", Key Engineering Materials, Vols. 467-469, pp. 2129-2136, 2011
Online since
February 2011
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Price
$35.00
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