A Hybrid GRASP Algorithm for an Integrated Production Planning and a Group Layout Design in a Dynamic Cellular Manufacturing System

• Published in: IEEE access Vol. 8; pp. 162809 - 162818
• Main Authors: Khamlichi, Hanane, Oufaska, Kenza, Zouadi, Tarik, Dkiouak, Rachid
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive search techniques; Algorithms; Cellular manufacture; Cellular manufacturing; Configurations; DCMS; GRASP; Group layout design; Heuristic algorithms; Integer programming; Layout; Layouts; Linear programming; lot-sizing; Manufacturing cells; Materials handling; Mathematical model; Mixed integer; Planning; Production planning; Relocation; Replenishment
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3018505

Demand fluctuations influence the configuration of manufacturing workshops. Integration of optimal production planning via the replenishment organization, can significantly reduce the excessive++reconfigurations number in each period and, thereafter, the global managing costs. In this article, we discuss the joint machines Group layout design (GLD) and lot-sizing problem (LSP) in a dynamic cellular manufacturing system (DCMS). We propose a novel multi-period model to determine the best cell formation, necessary configurations over each period, and optimal production and inventory policy that minimizes intra and inter-cell material handling, holding costs, and multitasks machines relocation. We propose a novel mixed-integer programming (MIP) associated model which is then solved by using the commercial software Optimizer CPLEX. Additionally, we present a hybrid greedy randomized adaptive search procedure (GRASP) enhanced with a path relinking procedure (PR) to solve the problem. Computational results on several benchmarks and randomly generated instances show the effectiveness and the relevance of the proposed approach and highlight the integration value.