期刊
COMPUTERS & OPERATIONS RESEARCH
卷 132, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2021.105283
关键词
Facility layout design; Multi-objective optimisation; Genetic algorithm; Mixed integer linear programming; Variable neighbourhood search
类别
资金
- National Natural Science Foundation of China [51205328, 51675450]
- Youth Foundation for Humanities, Social Sciences of Ministry of Education of China [18YJC630255]
- Sichuan Science and Technology Program [2019YFG0285]
- China Scholarship Council [202007000083]
This study investigates the bi-objective double-floor corridor allocation problem using a mixed integer linear programming model and a genetic algorithm with a variable neighbourhood search technique, demonstrating superior performance through comparisons and updating lower bounds of benchmark instances.
The bi-objective double-floor corridor allocation problem (bDFCAP) investigated here explores the effective placement of given departments in a double-floor space to minimise the overall flow cost and the corridor length objectives. Within each floor, departments are arranged in two parallel rows on opposite sides along a central corridor without overlapping. In this study, the bDFCAP is formulated as a mixed integer linear programming model, which has improved the performance over the previous one. Thereafter, a genetic algorithm with a variable neighbourhood search technique is designed and employed to solve the bDFCAP in a more effective manner. This technique is utilized to improve the local search capability by adaptively transforming between a deep-searching strategy and broad-searching strategy, and the superior performance of the proposed method is proven through comparisons with two other algorithms in current literature. Besides, the state-of-the-art lower bounds of several benchmark instances are updated.
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