An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem
Autor: | Masood Fathi, Hamidreza Eskandari, Amir Nourmohammadi, Amos H. C. Ng, Anna Syberfeldt |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
Mathematical optimization Computer science Automotive industry 02 engineering and technology assembly line balancing Lean manufacturing Set (abstract data type) 020901 industrial engineering & automation generation transfer Genetic algorithm 0202 electrical engineering electronic engineering information engineering genetic algorithm Local search (optimization) Production Engineering Human Work Science and Ergonomics business.industry General Engineering Produktionsteknik arbetsvetenskap och ergonomi Workload Computer Science Applications Computational Theory and Mathematics Benchmark (computing) 020201 artificial intelligence & image processing business variable neighborhood search Software Variable neighborhood search |
Zdroj: | Engineering Computations |
Popis: | Purpose This study aims to propose an efficient optimization algorithm to solve the assembly line balancing problem (ALBP). The ALBP arises in high-volume, lean production systems when decision-makers aim to design an efficient assembly line while satisfying a set of constraints. Design/methodology/approach An improved genetic algorithm (IGA) is proposed in this study to deal with ALBP to optimize the number of stations and the workload smoothness. Findings To evaluate the performance of the IGA, it is used to solve a set of well-known benchmark problems and a real-life problem faced by an automobile manufacturer. The solutions obtained are compared against two existing algorithms in the literature and the basic genetic algorithm. The comparisons show the high efficiency and effectiveness of the IGA in dealing with ALBPs. Originality/value The proposed IGA benefits from a novel generation transfer mechanism that improves the diversification capability of the algorithm by allowing population transfer between different generations. In addition, an effective variable neighborhood search is used in the IGA to enhance its local search capability. |
Databáze: | OpenAIRE |
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