Optimizing vehicle routing is a key step to reduce the carbon emissions in the transportation industry, which is an important goal for achieving national sustainable development. So multi-objective vehicle routing problem is studied under low carbon emission. In this paper, we propose a multi-objective mixed-integer programming model to minimize the number of vehicles, travel distance, and carbon emission costs by considering each vehicle's loading capacity and the number of customers served. The NSGA-II is designed for solving the model, and the effectiveness of the algorithm is verified by the actual example of the SH logistics company. It is shown that the carbon emission costs are reduced by 2.45%, and the total travel distance is reduced by 14.21% after comparing the optimized result and the former one. The research results of this paper provide a decision basis for logistics companies to plan routes under a low-carbon background.
Multi-Objective Vehicle Routing Problem Based on NSGA-II
27.09.2020
4104523 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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