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

Bing Gang Wang

doi:10.4028/www.scientific.net/AMR.566.253

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 566Sequencing Mixed-Model Assembly Lines to Minimize...

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

Abstract:

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.

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Periodical:

Advanced Materials Research (Volume 566)

Pages:

253-256

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.566.253

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Online since:

September 2012

Authors:

Bing Gang Wang

Keywords:

Hybrid Genetic Algorithm, Mixed-Model Assembly Lines, Sequencing, Variation of Parts Consumption

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