A hybrid genetic algorithm approach to mixed-model assembly line balancing |
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Authors: | A Noorul Haq K Rengarajan J Jayaprakash |
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Affiliation: | (1) Department of Production Engineering, National Institute of Technology, Tiruchirapalli, 620 015, India;(2) Department of Mechanical Engineering, Pachari Sri Nallathankal Amman (PSNA) College of Engineering and Technology, Dindigul, 624 622, India |
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Abstract: | Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass
production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product
variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is
intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This
study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize
the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified
ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search
time. Several examples illustrate the approach. The software used for programming is C++ language . |
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Keywords: | Genetic algorithm Hybrid algorithm Mixed-model assembly line balancing |
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