Return
Deviation-flow refueling location problem with capacitated facilities: Model and algorithm
DOI:10.1016/j.trd.2017.05.015.png)
Abstract
En 中文
At the beginning of the period of transition from petroleum-based fuels to alternative green fuels, determining the optimal location of alternative fuel stations (AFSs) would be an important task. This paper addresses this issue under two main assumptions. First, the capacity of AFSs is limited and each AFS can only serve a number of vehicles up to its capacity. Second, drivers may have to deviate from their pre-determined shortest path to get refueling services. This problem is formulated as a mixed integer linear programming (MILP) model and a heuristic algorithm is developed to solve it. The heuristic method involves solving small and easy to solve linear programing (LP) models, embedded within a greedy approach, and hence, it requires an LP software. Although the proposed MILP model requires that the set of deviation paths be pregenerated with respect to the maximum tolerated deviation distance, the heuristic uses only a restricted set of such paths. The performance of the proposed model and algorithm is evaluated on some randomly generated instances. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords:
Deviation-flow
Alternative fuel vehicles
Capacitated station
Mixed integer programming
Heuristic method
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.7
Papers:
4.5K
Citations:
2.5W
Organization
Cited Papers
Refueling availability for alternative fuel vehicle markets: Sufficient urban station coverage
ENERGY POLICY
IF9.2
Desire and Dread from the Nucleus Accumbens: Cortical Glutamate and Subcortical GABA Differentially Generate Motivation and Hedonic Impact in the Rat
PLoS ONE
IF0

