A hybrid ACS-VTM algorithm for the vehicle routing problem with simultaneous delivery & pickup and real-time traffic condition
•A mixed integer programming model for the VRPSDPTI.•A hybrid algorithm of ant colony system and virtual transformation method (ACS-VTM).•A practical case to verify the model and algorithm and to provide managerial insights.•The hybrid ACS-VTM algorithm effectively reduce total travel cycle for the...
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| Vydané v: | Computers & industrial engineering Ročník 162; s. 107747 |
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| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.12.2021
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| ISSN: | 0360-8352, 1879-0550 |
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| Abstract | •A mixed integer programming model for the VRPSDPTI.•A hybrid algorithm of ant colony system and virtual transformation method (ACS-VTM).•A practical case to verify the model and algorithm and to provide managerial insights.•The hybrid ACS-VTM algorithm effectively reduce total travel cycle for the VRPSDPTI.
The vehicle routing problem with simultaneous delivery & pickup and real-time traffic information (VRPSDPTI) is a dynamic problem of combinatorial network optimisation in logistics and supply chain management. It is also a typical NP-hard problem that has plagued enterprises with reverse logistics operations for many years. The main objective of this research is to determine an optimal vehicle routing plan for the VRPSDPTI problem. To achieve this goal, a mixed integer programming (MIP) model is constructed, with the objective of minimising the total travel cycle for the VRPSDPTI problem. A hybrid algorithm of the ant colony system and virtual transformation method (ACS-VTM) is then designed to explore the vehicle routing plan for the VRPSDPTI problem; it adopts a flexible split of the time period for re-optimisation and an improved partial service policy for customer demand. Based on it, a practical case of the VRPSDPTI problem is used to verify the proposed model and algorithm. One major finding is proposed through the study of the practical case that adopting the hybrid ACS-VTM algorithm can effectively reduce the total travel cycle for the VRPSDPTI problem. The main contributions of this study are that it can provide an efficient decision tool to solve the VRPSDPTI, and can not only reduce the total travel cycle, but also improve the efficiency of vehicle utilisation. |
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| AbstractList | •A mixed integer programming model for the VRPSDPTI.•A hybrid algorithm of ant colony system and virtual transformation method (ACS-VTM).•A practical case to verify the model and algorithm and to provide managerial insights.•The hybrid ACS-VTM algorithm effectively reduce total travel cycle for the VRPSDPTI.
The vehicle routing problem with simultaneous delivery & pickup and real-time traffic information (VRPSDPTI) is a dynamic problem of combinatorial network optimisation in logistics and supply chain management. It is also a typical NP-hard problem that has plagued enterprises with reverse logistics operations for many years. The main objective of this research is to determine an optimal vehicle routing plan for the VRPSDPTI problem. To achieve this goal, a mixed integer programming (MIP) model is constructed, with the objective of minimising the total travel cycle for the VRPSDPTI problem. A hybrid algorithm of the ant colony system and virtual transformation method (ACS-VTM) is then designed to explore the vehicle routing plan for the VRPSDPTI problem; it adopts a flexible split of the time period for re-optimisation and an improved partial service policy for customer demand. Based on it, a practical case of the VRPSDPTI problem is used to verify the proposed model and algorithm. One major finding is proposed through the study of the practical case that adopting the hybrid ACS-VTM algorithm can effectively reduce the total travel cycle for the VRPSDPTI problem. The main contributions of this study are that it can provide an efficient decision tool to solve the VRPSDPTI, and can not only reduce the total travel cycle, but also improve the efficiency of vehicle utilisation. |
| ArticleNumber | 107747 |
| Author | Xie, Naiming Zhou, Yutong Liu, Wei Chen, Jian Liu, Wenjie Qiu, Jing Chang, Xiangyun |
| Author_xml | – sequence: 1 givenname: Wenjie surname: Liu fullname: Liu, Wenjie email: lwj751231@nuaa.edu.cn organization: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 2 givenname: Yutong surname: Zhou fullname: Zhou, Yutong organization: Department of Industrial Engineering, School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150006, China – sequence: 3 givenname: Wei surname: Liu fullname: Liu, Wei organization: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 4 givenname: Jing surname: Qiu fullname: Qiu, Jing organization: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 5 givenname: Naiming surname: Xie fullname: Xie, Naiming organization: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 6 givenname: Xiangyun surname: Chang fullname: Chang, Xiangyun organization: Department of Management Science and Engineering, East China University of Science and Technology, Shanghai 200237, China – sequence: 7 givenname: Jian surname: Chen fullname: Chen, Jian organization: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China |
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| Keywords | Virtual transformation method Vehicle routing plan Ant colony system algorithm Real-time traffic conditions Hybrid algorithm Vehicle routing problem with simultaneous delivery & pickup |
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