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Article type: Research Article
Authors: Ferdowsi, Farzaneha | Maleki, Hamid Rezaa; * | Niroomand, Sadeghb
Affiliations: [a] Faculty of Mathematics, Shiraz University of Technology, Shiraz, Iran | [b] Department of Industrial Engineering, Eastern Mediterranean University, Famagusta, Mersin, Turkey; Department of Industrial Engineering, Firouzabad Institute of Higher Education, Firouzabad, Fars, Iran
Correspondence: [*] Corresponding author. Hamid Reza Maleki, Faculty of Mathematics, Shiraz University of Technology, P.O. Box 71555-313, Shiraz, Iran. Tel.: +98 71 37261392; Fax: +98 71 37354523; E-mail: [email protected].
Abstract: In order to decrease the environmental pollution, automotive industries have considered the production of alternative fuel vehicles using mainly gas-based fuels. These vehicles need more refueling in a given path compared to the fossil fuel based vehicles, because of their limited fuel tank capacity. In such vehicles, the drivers’ convenience is increased by using intelligent transportation systems which help them to find a suitable travel path, refueling stations, etc. In this paper, a new problem with a fuzzy bi-objective formulation is proposed to select on where to refuel a vehicle in order to have a minimum total cost of refueling as well as a minimum number of necessary refueling where the fuel consumption is of fuzzy values. To solve such problem, after converting the fuzzy formulation to a crisp form by using the credibility measure, a new hybrid fuzzy interactive approach is proposed. The computational study on a real case from Turkey demonstrates that the proposed method performs mainly either better or the same as the methods of the literature. The solution obtained by the proposed model can be given to an intelligent system installed on the vehicles to do intelligent planning for where to refuel the vehicle.
Keywords: Multi-objective optimization, refueling cost, alternative fuel vehicle, credibility measure, interactive fuzzy programming
DOI: 10.3233/JIFS-171471
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2385-2399, 2018
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