Optimizing Number and Locations of Alternative-Fuel Stations Using a Multi-Criteria Approach

Abstract

The transition to alternative fuels is obligatory due to the finite amount of available fossil fuels and their rising prices. However, the transition cannot be done unless enough infrastructure exists. A very important infrastructure is the fueling station. As establishing alternative-fuel stations is expensive, the problem of finding the optimal number and locations of initial alternative-fuel stations emerges and it is investigated in this paper. A mixed-integer linear programming (MILP) formulation is proposed to minimize the costs using net present value (NPV) technique. The proposed formulation considers the criteria of the two most common models in the literature for such a problem, namely P-median model and flow refueling location model (FRLM). A decision support system is developed for the users to be able to control the parameter values and run different scenarios. For case study purposes, the method is used to find the optimal number and locations of the alternative-fuel stations in the city of Chicago. Some data wrangling techniques are used to overcome the inability of the method to solve very large-scale problems.