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Original scientific paper

https://doi.org/10.17559/TV-20200809211109

Low Carbon Logistics Optimization for Multi-depot CVRP with Backhauls - Model and Solution

Xiaoning Zhu* ; Donlinks School of Economics and Management, University of Science & Technology Beijing, Beijing 100083, China
Ziqian Zhao ; Donlinks School of Economics and Management, University of Science & Technology Beijing, Beijing 100083, China
Rui Yan ; Donlinks School of Economics and Management, University of Science & Technology Beijing, Beijing 100083, China; School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China


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Abstract

CVRP (Capacitated Vehicle Routing Problems) is the integrated optimization of VRP and Bin Packing Problem (BPP), which has far-reaching practical significance, because only by taking both loading and routing into consideration can we make sure the delivery route is the most economic and the items are completely and reasonably loaded into the vehicles. In this paper, the CVRP with backhauls from multiple depots is addressed from the low carbon perspective. The problem calls for the minimization of the carbon emissions of a fleet of vehicles needed for the delivery of the items demanded by the clients. The overall problem, denoted as 2L-MDCVRPB, is NP-hard and it is very difficult to get a good performance solution in practice. We propose a quantum-behaved particle swarm optimization (QPSO) and exploration heuristic local search algorithm (EHLSA) in order to solve this model. In addition, three groups of computational experiments based on well-known benchmark instances are carried out to test the efficiency and effectiveness of the proposed model and algorithm, thereby demonstrating that the proposed method takes a short computing time to generate high quality solutions. For some instances, our algorithm can obtain new better solutions.

Keywords

capacitated vehicle routing problem; hybrid algorithm; low carbon

Hrčak ID:

244782

URI

https://hrcak.srce.hr/244782

Publication date:

17.10.2020.

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