Routing strategies for efficient deployment of alternative fuel vehicles for freight delivery.
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Routing strategies for efficient deployment of alternative fuel vehicles for freight delivery.

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      With increasing concerns on environmental issues, recent research on Vehicle Routing Problems (VRP) has added new factors such as greenhouse gas emissions and alternative fuel vehicles into the models. In this report, we consider one such promising alternative fuel vehicle, Compressed Natural Gas (CNG). However, due to the limited number of available fueling stations and small fuel tank capacity, CNG trucks face several challenges on their way to replacing traditional diesel trucks. Even though CNG trucks have advantages on less greenhouse gas emissions and cheaper fuel cost, the detours to the fueling station may increase the total travel distance. We introduce the CNG Truck Routing Problem with Fueling Stations (CTRPFS) to model decisions to be made with regards to the vehicle routes including the choice of fueling stations. Moreover we consider load capacity, fuel tank capacity and the driver’s daily traveling distance limitation. We develop a Mixed Integer Programming (MIP) model with preprocessing and valid inequalities to solve the problem optimally. A hybrid heuristic method is also proposed to solve this problem, which combines an Adaptive Large Neighborhood Search (ALNS) with a local search and a MIP model. In the numerical experiments section, we solve a set of small instances to show the efficiency of our preprocessing and valid inequalities. The optimal values from MIP models are used as benchmarks to show our ALNS can achieve high quality solutions. We run experiments on large instances to explore some insights on the number of CNG fueling stations and tank capacities. Based on the estimation of daily goods delivery data from the Ports of Los Angeles and Long Beach, we conduct experiments comparing the total traveling distance using CNG trucks with the current use of diesel trucks for local delivery.
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