A Hesitant Fuzzy Linguistic Terms Set-Based AHP and TOPSIS Methodology for Fuel Coal Type Selection Problem of Industrial Facilities

Abstract

Coal is still used widely by both industrial facilities and coal fired power plants. Lignite, hard coal, coke, and imported coal are some alternatives. The coal has ash content, moisture content, heat rate, volatile matter, carbon content, sulphur content, and size that need to be considered as well as price. The suppliers provide coal products for each coal type, and the most appropriate coal product needs to be selected considering different parameters. Therefore, in this paper, a hesitant fuzzy linguistic term sets-based AHP (HFLTS-AHP) and TOPSIS method are used to select the best coal type alternative for industrial facilities. As the HFLTS-AHP is used to weight the evaluation criteria, TOPSIS is utilized to rank the fuel coal type alternatives. The proposed methodology offers an innovative and novel approach to help industrial facilities select the appropriate coal product while balancing the outputs, such as carbon, sulphur, ash content, and so on. In another point of view, the motivation of this research is to help industrial firms find out the ultimate fuel coal alternative based on their needs. This objective is realized using the proposed approach that integrates the HFLTS-AHP and TOPSIS approaches for the related problem, also utilizing group decision making. Moreover, this approach is concreted by an Excel template that provides an effective tool for firms to realize the evaluation process without many tiresome fuzzy comparisons and complex calculations. Furthermore, in the paper, a real-life case study in Turkish industrial facilities is presented to demonstrate the effectiveness and applicability of the proposed approach to readers and practitioners. In this case, seven coal type options are evaluated in terms of eight criteria by three decision makers, and the best coal type alternative is determined.