An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution
A variant of the vehicle routing problem (VRP) known as the Vehicle Routing Problem in Omnichannel Retailing Distribution Systems (VRPO) has recently been introduced in the literature, driven by the increasing adoption of omnichannel logistics in practice. The VRPO scenario involves a large retailer...
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MDPI AG
2024-11-01
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| Series: | Mathematics |
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| author | Vincent F. Yu Ching-Hsuan Lin Renan S. Maglasang Shih-Wei Lin Kuan-Fu Chen |
| author_facet | Vincent F. Yu Ching-Hsuan Lin Renan S. Maglasang Shih-Wei Lin Kuan-Fu Chen |
| author_sort | Vincent F. Yu |
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| description | A variant of the vehicle routing problem (VRP) known as the Vehicle Routing Problem in Omnichannel Retailing Distribution Systems (VRPO) has recently been introduced in the literature, driven by the increasing adoption of omnichannel logistics in practice. The VRPO scenario involves a large retailer managing several stores, a depot, and a homogenous fleet of vehicles to meet the demands of both stores and online customers. This variant falls within the class of VRPs that consider precedence constraints. Although the vehicle routing problem in omnichannel retailing distribution (VRPO) has been addressed using a few heuristic and metaheuristic approaches, the use of Simulated Annealing (SA) remains largely unexplored in the pickup and delivery problem (PDP) literature, both before and after the rise of omnichannel logistics. This article introduces the Efficient Simulated Annealing (ESA) algorithm, demonstrating its suitability in generating new benchmark solutions for the VRPO. In experiments with sixty large instances, ESA significantly outperformed two previous algorithms, discovering new best-known solutions (BKSs) in fifty-nine out of sixty cases. Additionally, ESA demonstrated superior efficiency in 68.3% of the test cases in terms of reduced computational times, showcasing its higher effectiveness in handling complex VRPO instances. |
| format | Article |
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| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Mathematics |
| spelling | doaj-art-a65bcaa67a2c4d30b6d5bac954e1f0aa2024-12-13T16:27:21ZengMDPI AGMathematics2227-73902024-11-011223366410.3390/math12233664An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel DistributionVincent F. Yu0Ching-Hsuan Lin1Renan S. Maglasang2Shih-Wei Lin3Kuan-Fu Chen4Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, TaiwanDepartment of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, TaiwanDepartment of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, TaiwanDepartment of Information Management, Chang Gung University, Taoyuan 333, TaiwanDepartment of Emergency Medicine, Keelung Chang Gung Memorial Hospital, Keelung 204, TaiwanA variant of the vehicle routing problem (VRP) known as the Vehicle Routing Problem in Omnichannel Retailing Distribution Systems (VRPO) has recently been introduced in the literature, driven by the increasing adoption of omnichannel logistics in practice. The VRPO scenario involves a large retailer managing several stores, a depot, and a homogenous fleet of vehicles to meet the demands of both stores and online customers. This variant falls within the class of VRPs that consider precedence constraints. Although the vehicle routing problem in omnichannel retailing distribution (VRPO) has been addressed using a few heuristic and metaheuristic approaches, the use of Simulated Annealing (SA) remains largely unexplored in the pickup and delivery problem (PDP) literature, both before and after the rise of omnichannel logistics. This article introduces the Efficient Simulated Annealing (ESA) algorithm, demonstrating its suitability in generating new benchmark solutions for the VRPO. In experiments with sixty large instances, ESA significantly outperformed two previous algorithms, discovering new best-known solutions (BKSs) in fifty-nine out of sixty cases. Additionally, ESA demonstrated superior efficiency in 68.3% of the test cases in terms of reduced computational times, showcasing its higher effectiveness in handling complex VRPO instances.https://www.mdpi.com/2227-7390/12/23/3664vehicle routing problempickup and deliverysimulated annealingmetaheuristicsomnichannel distribution |
| spellingShingle | Vincent F. Yu Ching-Hsuan Lin Renan S. Maglasang Shih-Wei Lin Kuan-Fu Chen An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution Mathematics vehicle routing problem pickup and delivery simulated annealing metaheuristics omnichannel distribution |
| title | An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution |
| title_full | An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution |
| title_fullStr | An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution |
| title_full_unstemmed | An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution |
| title_short | An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution |
| title_sort | efficient simulated annealing algorithm for the vehicle routing problem in omnichannel distribution |
| topic | vehicle routing problem pickup and delivery simulated annealing metaheuristics omnichannel distribution |
| url | https://www.mdpi.com/2227-7390/12/23/3664 |
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