Multi-Objective Material Logistics Planning with Discrete Split Deliveries Using a Hybrid NSGA-II Algorithm

Weikang Fang, Zailin Guan, Peiyue Su, Dan Luo, Linshan Ding and Lei Yue ()
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Weikang Fang: State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Zailin Guan: State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Peiyue Su: State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Dan Luo: State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Linshan Ding: State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Lei Yue: School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China

Mathematics, 2022, vol. 10, issue 16, 1-30

Abstract: To schedule material supply intelligently and meet the production demand, studies concerning the material logistics planning problem are essential. In this paper, we consider the problem based on the scenario that more than one vehicle may visit each station in batches. The primary objective is to satisfy the demands in the time windows, followed by logistics planning with the minimum vehicles and travel time as the optimization objective. We construct a multi-objective mixed-integer programming model for the scenario of discrete material supply in workshops. First, we propose a hybrid heuristic algorithm combining NSGA-II and variable neighborhood search. This proposed algorithm combines the global search capability of NSGA-II and the strong local search capability, which can balance intensification and diversification well. Second, to maintain the diversity of population, we design the population diversity strategy and various neighborhood operators. We verify the effectiveness of the hybrid algorithm by comparing with other algorithms. To test the validity of the proposed problem, we have carried out research and application in a construction machinery enterprise.

Keywords: material logistics planning; multi-objective optimization; split delivery by batch; mixed-integer linear programming; hybrid algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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