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http://dx.doi.org/10.7737/JKORMS.2012.37.3.039

An Endosymbiotic Evolutionary Algorithm for Balancing and Sequencing in Mixed-Model Two-Sided Assembly Lines  

Jo, Jun-Young (전남대학교 공과대학 산업공학과)
Kim, Yeo-Keun (전남대학교 공과대학 산업공학과)
Publication Information
Journal of the Korean Operations Research and Management Science Society / v.37, no.3, 2012 , pp. 39-55 More about this Journal
Abstract
This paper presents an endosymbiotic evolutionary algorithm (EEA) to solve both problems of line balancing and model sequencing in a mixed-model two-sided assembly line (MMtAL) simultaneously. It is important to have a proper balancing and model sequencing for an efficient operation of MMtAL. EEA imitates the natural evolution process of endosymbionts, which is an extension of existing symbiotic evolutionary algorithms. It provides a proper balance between parallel search with the separated individuals representing partial solutions and integrated search with endosymbionts representing entire solutions. The strategy of localized coevolution and the concept of steady-state genetic algorithms are used to improve the search efficiency. The experimental results reveal that EEA is better than two compared symbiotic evolutionary algorithms as well as a traditional genetic algorithm in solution quality.
Keywords
Two-Sided Assembly Line; Mixed Models; Balancing and Sequencing Problem; Endosymbiotic Evolutionary Algorithm; Endosymbionts;
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Times Cited By KSCI : 1  (Citation Analysis)
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