Research on Balancing Problem of Stochastic Two-Sided Mixed-Model Assembly Lines

Beibei Zhang () and Dan Chang ()
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Beibei Zhang: Beijing Jiaotong University
Dan Chang: Beijing Jiaotong University

A chapter in LISS 2020, 2021, pp 963-980 from Springer

Abstract: Abstract In the design of assembly lines in industrial systems, the adoption of two or more assembly lines is a method to realize high efficiency, which is called parallel assembly lines. In addition, the occurrence of stochastic events in industrial systems is inevitable, thus it is more realistic to regard industrial system as the stochastic environment. For this reason, this article proposes a mathematical model of stochastic mixed-model two-sided assembly line balancing problem (STMALBP), and adopts a genetic algorithm based on feasible sequence real-number encoding to solve STMALBP. The feasibility and effectiveness of the model and algorithm are verified by classical calculating examples, and the proposed algorithm is applied to balance the actual mixed-model assembly line with normal distribution operation time, which provides a valuable reference for the research of assembly line balancing.

Keywords: Assembly line balancing problem; Genetic algorithm; Stochastic two-sided assembly line (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-33-4359-7_66

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DOI: 10.1007/978-981-33-4359-7_66

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