期刊
PLOS ONE
卷 13, 期 2, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0192000
关键词
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资金
- Central South University Teacher Research Fund [2015JSJJ001]
- Hunan Province Science and Technology Development Funds [2015RS4045]
- Hunan Provincial Department of Education [15B261]
- National Natural Science Foundation of China [71672193]
Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large-or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions.
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