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A mathematical model and genetic algorithm-based approach for parallel two-sided assembly line balancing problem
Authors:Ibrahim Kucukkoc  David Z Zhang
Institution:1. College of Engineering, Mathematics and Physical Sciences, University of Exeter, Streatham Campus, North Park Road, EX4 4QF Exeter, England, UK;2. Faculty of Engineering and Architecture, Department of Industrial Engineering, Balikesir University, Cagis Campus, 10145 Balikesir, Turkeyi.kucukkoc@exeter.ac.ukikucukkoc@balikesir.edu.tr
Abstract:Assembly lines are usually constructed as the last stage of the entire production system and efficiency of an assembly line is one of the most important factors which affect the performance of a complex production system. The main purpose of this paper is to mathematically formulate and to provide an insight for modelling the parallel two-sided assembly line balancing problem, where two or more two-sided assembly lines are constructed in parallel to each other. We also propose a new genetic algorithm (GA)-based approach in alternatively to the existing only solution approach in the literature, which is a tabu search algorithm. To the best of our knowledge, this is the first formal presentation of the problem as well as the proposed algorithm is the first attempt to solve the problem with a GA-based approach in the literature. The proposed approach is illustrated with an example to explain the procedures of the algorithm. Test problems are solved and promising results are obtained. Statistical tests are designed to analyse the advantage of line parallelisation in two-sided assembly lines through obtained test results. The response of the overall system to the changes in the cycle times of the parallel lines is also analysed through test problems for the first time in the literature.
Keywords:parallel two-sided assembly lines  assembly line balancing  production planning  genetic algorithm  meta-heuristics  artificial intelligence
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