Abstract
The capacitated vehicle routing problem is a very classic but simple type of vehicle routing problem (VRP). There are variants of the VRP in practice based on different constraints which are called rich VRP (RVRP). In this article, variants of the VRP, including fixed vehicle types and dynamic vehicle type combinations are analyzed. An improved ant colony optimization (ACO) algorithm is designed to resolve this group of VRPs. The fixed vehicle type VRP, homogenous fleet VRP and heterogeneous fleet VRP are defined by one or multiple vehicle types in RVRP. Because of the evolution of transportation equipment, some new vehicle types such as truck and full trailer as well as tractor and semitrailer are introduced. The static and dynamic usages of different vehicle types vary with the business operations. We define this kind of VRPs as full-vehicle-mode (FVM) VRP in this paper. The associated ACO algorithm is developed to solve FVM-VRP problems. Computational experiments are performed and the results are presented to demonstrate the efficiency of the proposed algorithm.
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Acknowledgements
We are indebted to Prof. Stefan Voss and three anonymous reviewers for insightful observations and suggestions that have helped to improve our paper This work was partially supported by NSFC of China project [grant number 41771410], CIUC and TJAD [grant number CIUC20150011].
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Liu, Y., Cao, B. (2018). Solving Full-Vehicle-Mode Vehicle Routing Problems Using ACO. In: Cerulli, R., Raiconi, A., Voß, S. (eds) Computational Logistics. ICCL 2018. Lecture Notes in Computer Science(), vol 11184. Springer, Cham. https://doi.org/10.1007/978-3-030-00898-7_20
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DOI: https://doi.org/10.1007/978-3-030-00898-7_20
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