Product family assembly line balancing based on an improved genetic algorithm

Product family assembly line (PFAL) is a mixed-model assembly line on which a family of similar products can be assembled at the same time. Aiming at the balance problem of PFAL, a balancing model for PFAL is established, and simultaneously an improved dual-population genetic algorithm is proposed....

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Bibliographic Details
Published inInternational journal of advanced manufacturing technology Vol. 70; no. 9-12; pp. 1775 - 1786
Main Authors Hou, Liang, Wu, Yong-ming, Lai, Rong-shen, Tsai, Chi-Tay
Format Journal Article
LanguageEnglish
Published London Springer London 01.02.2014
Springer Nature B.V
Subjects
Assembly lines
Balancing
CAE) and Design
Classification
Computer-Aided Engineering (CAD
Decoding
Engineering
Genetic algorithms
Industrial and Production Engineering
Loaders
Mechanical Engineering
Media Management
Optimization
Original Article
Performance indices
Sequential scheduling
Sorting algorithms
Stations
Optimal balancing
Product family
Assembly line
Genetic algorithm
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Summary:Product family assembly line (PFAL) is a mixed-model assembly line on which a family of similar products can be assembled at the same time. Aiming at the balance problem of PFAL, a balancing model for PFAL is established, and simultaneously an improved dual-population genetic algorithm is proposed. Firstly, through the characteristic analysis of PFAL, the tasks on PFAL are divided into three categories, namely the common, optional, and personality tasks. In addition, the correlation between the tasks is mainly considered. In the improved genetic algorithm, minimizing the number of stations, minimizing the load indexes between stations and within each station, and maximizing task-related degree are used as optimization objectives. In the initialization process, a method based on a TOP sorting algorithm is adopted for generating chromosomes. Furthermore, a new decoding algorithm is proposed to make up for the lack of the traditional decoding method, and individuals in the two populations are exchanged. Therefore, the search speed of the algorithm is accelerated, which shows good performance through classic tested problems. Finally, the effectiveness and feasibility of the method were validated by optimizing assembly line balancing of loaders.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-013-5425-8