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

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  • Abstract:
    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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    urn:sha-512:ddb4d1fd7f1daed00ee61970025ea6a736abcaa3c9394d9a92c1423e85b2504f503de9ec43eabbfb5e4e65e45201b8938deb393448381cc690cbf51ef104ae35
File Language:
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