A Hybrid Genetic Algorithm for Integrated Truck Scheduling and Product Routing on the Cross-Docking System with Multiple Receiving and Shipping Docks
In this research, a truck scheduling problem for a cross-docking system with multiple receiving and shipping docks is studied. Until recently, single-dock cross-docking problems are studied mostly. This research is focused on the multiple-dock problems. The objective of the problem is to determine t...
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| Veröffentlicht in: | Mathematical problems in engineering 2021, Vol.2021, p.1-17 |
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| container_title | Mathematical problems in engineering |
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| creator | Yu, Wooyeon Ha, Chunghun Park, SeJoon |
| description | In this research, a truck scheduling problem for a cross-docking system with multiple receiving and shipping docks is studied. Until recently, single-dock cross-docking problems are studied mostly. This research is focused on the multiple-dock problems. The objective of the problem is to determine the best docking sequences of inbound and outbound trucks to the receiving and shipping docks, respectively, which minimize the maximal completion time. We propose a new hybrid genetic algorithm to solve this problem. This genetic algorithm improves the solution quality through the population scheme of the nested structure and the new product routing heuristic. To avoid unnecessary infeasible solutions, a linked-chromosome representation is used to link the inbound and outbound truck sequences, and locus-pairing crossovers and mutations for this representation are proposed. As a result of the evaluation of the benchmark problems, it shows that the proposed hybrid GA provides a superior solution compared to the existing heuristics. |
| doi_str_mv | 10.1155/2021/2026834 |
| format | Article |
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Until recently, single-dock cross-docking problems are studied mostly. This research is focused on the multiple-dock problems. The objective of the problem is to determine the best docking sequences of inbound and outbound trucks to the receiving and shipping docks, respectively, which minimize the maximal completion time. We propose a new hybrid genetic algorithm to solve this problem. This genetic algorithm improves the solution quality through the population scheme of the nested structure and the new product routing heuristic. To avoid unnecessary infeasible solutions, a linked-chromosome representation is used to link the inbound and outbound truck sequences, and locus-pairing crossovers and mutations for this representation are proposed. As a result of the evaluation of the benchmark problems, it shows that the proposed hybrid GA provides a superior solution compared to the existing heuristics.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2021/2026834</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Completion time ; Crossovers ; Docking ; Docks ; Genetic algorithms ; Heuristic ; Integer programming ; Literature reviews ; Logistics ; Mathematical problems ; Mathematical programming ; Optimization techniques ; Representations ; Scheduling ; Shipping ; Trucks</subject><ispartof>Mathematical problems in engineering, 2021, Vol.2021, p.1-17</ispartof><rights>Copyright © 2021 Wooyeon Yu et al.</rights><rights>Copyright © 2021 Wooyeon Yu et al. 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Until recently, single-dock cross-docking problems are studied mostly. This research is focused on the multiple-dock problems. The objective of the problem is to determine the best docking sequences of inbound and outbound trucks to the receiving and shipping docks, respectively, which minimize the maximal completion time. We propose a new hybrid genetic algorithm to solve this problem. This genetic algorithm improves the solution quality through the population scheme of the nested structure and the new product routing heuristic. To avoid unnecessary infeasible solutions, a linked-chromosome representation is used to link the inbound and outbound truck sequences, and locus-pairing crossovers and mutations for this representation are proposed. 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| subjects | Completion time Crossovers Docking Docks Genetic algorithms Heuristic Integer programming Literature reviews Logistics Mathematical problems Mathematical programming Optimization techniques Representations Scheduling Shipping Trucks |
| title | A Hybrid Genetic Algorithm for Integrated Truck Scheduling and Product Routing on the Cross-Docking System with Multiple Receiving and Shipping Docks |
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