Mathematical formulation and a new metaheuristic for the constrained double-floor corridor allocation problem. (October 2021)

• Record Type: Journal Article
• Authors: Liu, Silu; Zhang, Zeqiang; Guan, Chao; Liu, Junqi; Dewil, Reginald
• Is Part Of: Journal of manufacturing systems. Volume 61(2021)
• Page Start: 155
• Page End: 170
• Publication Date: 2021-10
• Subjects: Constrained facility layout -- Corridor allocation problem -- Multi-floor layout problem -- Mixed-integer programming model -- Metaheuristic; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2021.08.013
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: We consider a double floor CAP with seven types of facility constraints. A MILP model for the cDFCAP is built which can solve small-sized instances with 10 ≤ n ≤ 15 optimally within acceptable times using the CPLEX solver. An efficient metaheuristic optimisation algorithm has been designed for the cDFCAP. Numerous computational experiments of sizes varying from 10 to 80 are executed. Abstract: A layout plan for a manufacturing system that is designed without any facility constraints will most likely be infeasible when confronted with reality. Additionally, considering that land available for building industrial plants is limited and its cost is high, it is necessary to investigate the layout planning of two and multi-floor facilities. To address these shortages in the scientific literature, we focus on the double-floor corridor allocation problem (DFCAP) which covers a wide range of complex facility constraints, such as fixed floor constraints, fixed row constraints, fixed positioning constraints, mutual floor constraints, mutual row constraints, sequencing constraints and adjacency constraints. For the model mentioned above, we term it as a constrained DFCAP (cDFCAP). A mixed-integer linear programming model is formulated for the cDFCAP. In order to solve larger realistic problems, a constrained metaheuristic with the memetic algorithm framework customised for solving the cDFCAP is introduced in this work. In our algorithm, four problem-specific heuristic rules to construct a set of initial solutions are developed. In addition, an ideal parameter combination for our constrained memetic algorithm is determined through a Taguchi experimental design. Finally, the results of a set of cDFCAP instances with different sizes ( n = 10∼80) report that our provided approach is effective for the considered problem.