| Summary: | 碩士 === 國立成功大學 === 工業與資訊管理學系 === 105 === Conventional vehicle powered by fossil fuel has caused greenhouse effect for many years. Recently, the awareness of environmental protection inspires logis-tics using an alternative fuel vehicle (AFV) instead of a conventional vehicle for less CO2 emission. Among these AFV, the electric vehicle is popular and tech-nique mature which encourage logistics using it for city delivery. However, lim-ited refueling stations and driving range are disadvantages for electric vehicle. In this study, we formulate an integer programming model to minimize total travel time, vehicle idle time and charging time while considering vehicle loading, time window constraints and heterogeneous electric vehicle fleets. In solving phase we use record-to-record travel algorithm (RRT) with random remove, greedy insertion, 2-Opt and 2-Opt* to solve the large benchmark instances with three best RRT deviations 0.09, 0.07 and 0.05, we also find that solutions obtained by using these three parameters are similar, in which average total numbers of vehicle used in parameters 0.07 and 0.05 are the same but the total costs are different, this is because the rate of each vehicle type being used impact on the total cost.
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