Abstract
The world’s dependence on oil and gas has been increasing as global economies and infrastructure continue to rely heavily on petroleum-based products. Thus, there is a significant increase in the number of stations to meet the growing needs of the world. In this study, we concentrate on the location evaluation and selection problem of an oil station. Location selection of an oil & gas station is a Multiple Criteria Decision Making (MCDM) problem comprising several quantitative & qualitative criteria such as environmental, economic, and traffic related factors. In the literature, there are a number of studies focusing on oil-gas station location selection problem using different MCDM methods. The literature review has pointed out that traditional methods for location selection are insufficient for dealing with the indefinite or uncertain nature of linguistic assessment. Thus, considering uncertainties and subjectivity in human judgments, many researchers have been solving the multicriteria decision making problems employing MCDM methods based on the fuzzy sets. There are many extensions of the fuzzy sets such as Type-2, Hesitant, Pythagorean, and Neutrosophic fuzzy sets. In this study, a recently popular extension namely Spherical fuzzy set is used for solving a real-life oil station location evaluation and selection problem. In the study, Spherical fuzzy Analytical Hierarchy Process (SF-AHP) and Spherical fuzzy Weighted Aggregated Sum Product ASsessment (SF-WASPAS) methods are proposed for the solution of the problem. Then, sensitivity analysis is performed.
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Otay, I., Atik, S. (2021). Multi-criteria Oil Station Location Evaluation Using Spherical AHP&WASPAS: A Real-Life Case Study. In: Kahraman, C., Cevik Onar, S., Oztaysi, B., Sari, I., Cebi, S., Tolga, A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197. Springer, Cham. https://doi.org/10.1007/978-3-030-51156-2_68
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DOI: https://doi.org/10.1007/978-3-030-51156-2_68
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