A Green Vehicle Routing Method for the Regional Logistics Center

• Published in: 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) pp. 71 - 75
• Main Authors: Leu, Jun-Der, Krischke, Andre, Lee, Yi-Ping, Lee, Larry Jung-Hsing, Huang, Yi-Wei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2018
• Subjects: Air pollution; Cargo flows modeling; Distribution planning; Fuels; Green products; Green Vehicle Routing Problem (GVRP); Logistics; Planning; Transportation; Vehicle routing; Vehicle routing problems (VRP)
• ISSN: 2157-362X
• DOI: 10.1109/IEEM.2018.8607739

A regional logistics center is to provide an effective distribution service using the least transportation capacity to fulfill local demands. According to the MOBILE5 Vehicle Emissions Model provided by the US Environmental Protection Agency, traveling distance and speed is significant influence factors to the carbon emissions of transportation. The logistics planning issues defined by mathematical planning models or by discrete mathematics methods, on which optimization algorithms or heuristics are developed. In reality, the traffic situations are not stable all the time. When facing traffic problems, vehicles move in low speed, in which situation the carbon emissions will increase. However, most of these models are static ones, which follow the assumptions of stable traffic and fixed traveling speed on the network so that a significant error might happened when they applied to the green logistics directly. Again, these models do not consider the issue of oil consumption and carbon emission caused by the dynamic traveling speed. In this research, the cargo flows modeling approach is developed to analyze the logistics planning scenario of the single logistics center to many demand depots in the market region, wherein both of distribution effectiveness and carbon emission will be well considered. The planning algorithms or heuristics was developed, and the computer simulation method was applied to validate the solution quality in terms of different transportation scales and traffic situations. Finally, the issue of integration of the developed methods within the framework of a logistics planning software is discussed.