An integrated bi-objective optimization model and improved genetic algorithm for vehicle routing problems with temporal and spatial constraints
Vehicle routing problem (VRP) is a typical and important combinatorial optimization problem, and is often involved with complicated temporal and spatial constraints in practice. In this paper, the VRP is formulated as an optimization model for minimizing the number of vehicles and the total transpor...
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| Published in | Journal of industrial and management optimization Vol. 16; no. 3; pp. 1203 - 1220 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Springfield
American Institute of Mathematical Sciences
01.05.2020
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| Online Access | Get full text |
| ISSN | 1553-166X 1547-5816 1553-166X |
| DOI | 10.3934/jimo.2018200 |
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| Abstract | Vehicle routing problem (VRP) is a typical and important combinatorial optimization problem, and is often involved with complicated temporal and spatial constraints in practice. In this paper, the VRP is formulated as an optimization model for minimizing the number of vehicles and the total transportation cost subject to constraints on loading plan, service time and weight capacity. The transportation cost consists of the rent charge of vehicles, fuel cost, and carbon tax. Owing to complexity of the built model, it is divided into two subproblems by a two-stage optimization approach: at the first stage, the number of vehicles is minimized, then the routing plan is optimized at the second stage. For solving the sequential subproblems, two correlated genetic algorithms are developed, which share the same initial population to reduce their computational costs. Numerical results indicate that the developed algorithms are efficient, and a number of important managerial insights are revealed from the model. |
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| AbstractList | Vehicle routing problem (VRP) is a typical and important combinatorial optimization problem, and is often involved with complicated temporal and spatial constraints in practice. In this paper, the VRP is formulated as an optimization model for minimizing the number of vehicles and the total transportation cost subject to constraints on loading plan, service time and weight capacity. The transportation cost consists of the rent charge of vehicles, fuel cost, and carbon tax. Owing to complexity of the built model, it is divided into two subproblems by a two-stage optimization approach: at the first stage, the number of vehicles is minimized, then the routing plan is optimized at the second stage. For solving the sequential subproblems, two correlated genetic algorithms are developed, which share the same initial population to reduce their computational costs. Numerical results indicate that the developed algorithms are efficient, and a number of important managerial insights are revealed from the model. |
| Author | Wan, Zhong Li, Jiao-Yan Hu, Xiao |
| Author_xml | – sequence: 1 givenname: Jiao-Yan surname: Li fullname: Li, Jiao-Yan email: wanmath@csu.edu.cn organization: School of Mathematics and Statistics, Central South University, Changsha, 410083, China;Hunan University of Commerce, Shool of Computer and Information Engineering, Changsha, 410205, China – sequence: 2 givenname: Xiao surname: Hu fullname: Hu, Xiao email: huxiao0813@foxmail.com organization: School of Mathematics and Statistics, Central South University, Changsha, 410083, China – sequence: 3 givenname: Zhong surname: Wan fullname: Wan, Zhong email: teacherljy@126.com organization: School of Mathematics and Statistics, Central South University, Changsha, 410083, China |
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| Cites_doi | 10.1016/j.ejor.2013.10.044 10.1016/j.ejor.2016.04.016 10.1287/mnsc.6.1.80 10.1016/j.cam.2016.09.014 10.1016/S0305-0548(03)00158-8 10.1007/s10107-007-0178-5 10.1016/j.cor.2014.10.007 10.3934/jimo.2017009 10.1016/j.apm.2016.06.054 10.1007/s11075-014-9866-4 10.1016/j.cam.2017.09.026 10.3934/jimo.2016.12.1215 |
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| Title | An integrated bi-objective optimization model and improved genetic algorithm for vehicle routing problems with temporal and spatial constraints |
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