A Memetic Algorithm for Mixed-Integer Optimization Problems

Evolutionary algorithms (EAs) are population-based global search methods. Memetic Algorithms (MAs) are hybrid EAs that combine genetic operators with local search methods. With global exploration and local exploitation in search space, MAs are capable of obtaining more high-quality solutions. On the...

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Published inApplied Mechanics and Materials Vol. 284-287; pp. 2970 - 2974
Main Author Lin, Yung Chien
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 25.01.2013
Subjects
Evolutionary Algorithm (EA)
Memetic Algorithm
Mixed-Integer Optimization
Online AccessGet full text
ISBN3037856122
9783037856123
ISSN1660-9336
1662-7482
1662-7482
DOI10.4028/www.scientific.net/AMM.284-287.2970

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Abstract Evolutionary algorithms (EAs) are population-based global search methods. Memetic Algorithms (MAs) are hybrid EAs that combine genetic operators with local search methods. With global exploration and local exploitation in search space, MAs are capable of obtaining more high-quality solutions. On the other hand, mixed-integer hybrid differential evolution (MIHDE), as an EA-based search algorithm, has been successfully applied to many mixed-integer optimization problems. In this paper, a memetic algorithm based on MIHDE is developed for solving mixed-integer constrained optimization problems. The proposed algorithm is implemented and tested on a benchmark mixed-integer constrained optimization problem. Experimental results show that the proposed algorithm can find a better optimal solution compared with some other search algorithms.
AbstractList Evolutionary algorithms (EAs) are population-based global search methods. Memetic Algorithms (MAs) are hybrid EAs that combine genetic operators with local search methods. With global exploration and local exploitation in search space, MAs are capable of obtaining more high-quality solutions. On the other hand, mixed-integer hybrid differential evolution (MIHDE), as an EA-based search algorithm, has been successfully applied to many mixed-integer optimization problems. In this paper, a memetic algorithm based on MIHDE is developed for solving mixed-integer constrained optimization problems. The proposed algorithm is implemented and tested on a benchmark mixed-integer constrained optimization problem. Experimental results show that the proposed algorithm can find a better optimal solution compared with some other search algorithms.
Author Lin, Yung Chien
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Cites_doi 10.1115/1.2912596
10.1093/comjnl/7.4.308
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10.1007/3-540-32363-5
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Memetic Algorithm
Mixed-Integer Optimization
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