Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line |
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Authors: | Zixiang Li Qiuhua Tang Peter Nielsen |
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Affiliation: | 1. Industrial Engineering Department, Wuhan University of Science and Technology, Wuhan, PR China;2. Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China;3. Department of Materials and Production, Aalborg University, Aalborg, Denmark |
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Abstract: | This article presents the first method to simultaneously balance and sequence robotic mixed-model assembly lines (RMALB/S), which involves three sub-problems: task assignment, model sequencing and robot allocation. A new mixed-integer programming model is developed to minimize makespan and, using CPLEX solver, small-size problems are solved for optimality. Two metaheuristics, the restarted simulated annealing algorithm and co-evolutionary algorithm, are developed and improved to address this NP-hard problem. The restarted simulated annealing method replaces the current temperature with a new temperature to restart the search process. The co-evolutionary method uses a restart mechanism to generate a new population by modifying several vectors simultaneously. The proposed algorithms are tested on a set of benchmark problems and compared with five other high-performing metaheuristics. The proposed algorithms outperform their original editions and the benchmarked methods. The proposed algorithms are able to solve the balancing and sequencing problem of a robotic mixed-model assembly line effectively and efficiently. |
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Keywords: | Assembly line balancing model sequencing robotic assembly line simulated annealing co-evolutionary algorithm |
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