Balancing mixed-model assembly lines with sequence-dependent tasks via hybrid genetic algorithm

2015 ◽  
Vol 65 (1) ◽  
pp. 83-107 ◽  
Author(s):  
Qiuhua Tang ◽  
Yanli Liang ◽  
Liping Zhang ◽  
Christodoulos A. Floudas ◽  
Xiaojun Cao
Keyword(s):  
Genetic Algorithm ◽  
Mixed Model ◽  
Hybrid Genetic Algorithm ◽  
Assembly Lines ◽  
Mixed Model Assembly Lines ◽  
Sequence Dependent ◽  
Dependent Tasks ◽  
Mixed Model Assembly

Sequencing Mixed-Model Assembly Lines to Minimize the Variation of Parts Consumption by Hybrid Genetic Algorithms

2012 ◽  
Vol 566 ◽  
pp. 253-256
Author(s):  
Bing Gang Wang
Keyword(s):  
Genetic Algorithm ◽  
Mixed Model ◽  
Hybrid Genetic Algorithm ◽  
Initial Population ◽  
Assembly Lines ◽  
Mixed Model Assembly Lines ◽  
Mutation Operators ◽  
Sequencing Problems ◽  
Crossover And Mutation ◽  
Mixed Model Assembly

This paper is concerned about the sequencing problems in mixed-model assembly lines. The optimization objective is to minimizing the variation of parts consumption. The mathematical models are put forward. Since the problem is NP-hard, a hybrid genetic algorithm is newly-designed for solving the models. In this algorithm, the new method of forming the initial population is presented, the hybrid crossover and mutation operators are adopted, and moreover, the adaptive probability values for performing the crossover and mutation operations are used. The optimization performance is compared between the hybrid genetic algorithm and a genetic algorithm proposed in early published literature. The computational results show that satisfactory solutions can be obtained by the hybrid genetic algorithm and it performs better in terms of solution’s quality.

A Modified Genetic Algorithm for Sequencing Problem in Mixed Model Assembly Lines

2013 ◽  
Vol 655-657 ◽  
pp. 1675-1681
Author(s):  
Shu Xu ◽  
Fu Ming Li
Keyword(s):  
Genetic Algorithm ◽  
Mixed Model ◽  
Assembly Lines ◽  
Sequencing Problem ◽  
Mixed Model Assembly Lines ◽  
Modified Genetic Algorithm ◽  
Good Ability ◽  
Sequencing Problems ◽  
Dependent Setup Times ◽  
Mixed Model Assembly

On the base of summarizing and contrasting the objectives of sequencing problem in mixed model assembly lines (MMAL) , and in consideration of the influence sequence-dependent setup times , a objective is proposed to minimize the total unfinished works and idle times over all jobs and stations . And the corresponding model is presented. To solve this model, a modified genetic algorithm is proposed to determine suitable sequences. Comparing with the Lingo 9 software, the proposed GA turns out to have a good ability to solve the sequencing problems.

The Improved Genetic Algorithm for Balancing Mixed-Model Assembly Line

2011 ◽  
Vol 127 ◽  
pp. 603-608
Author(s):  
Qiu Hua Tang ◽  
Yan Li Liang
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Mixed Model ◽  
Assembly Line Balancing ◽  
Improved Genetic Algorithm ◽  
Assembly Lines ◽  
Mixed Model Assembly Lines ◽  
Assembly Line Balancing Problem ◽  
Mixed Model Assembly Line ◽  
Mixed Model Assembly

Mixed-model assembly lines are become more and more important by producing different models of the same product on an assembly line. Aiming at the existing mixed-model assembly line balancing problem, first, two important objective functions for minimizing cycle time and workload variance were provided, and mathematical models were established. Furthermore, in order to obtain the optimal or near optimal solutions, an improved genetic algorithm was proposed with combined precedence graph. Finally, the experiment results illustrate the feasibility and validity of the proposed improved genetic algorithm.

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