Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

Abstract

Multi-criteria decision-making methods support decision makers in all stages of the decision-making process by providing useful data. However, criteria are not always certain as uncertainty is a feature of the real world. MCDM methods under uncertainty and fuzzy systems are accepted as suitable techniques in conflicting problems that cannot be represented by numerical values, in particular in energy analysis and planning. In this paper, a modified TOPSIS method for multi-criteria group decision-making with qualitative linguistic labels is proposed. This method addresses uncertainty considering different levels of precision. Each decision maker's judgment on the performance of alternatives with respect to each criterion is expressed by qualitative linguistic labels. The new method takes into account linguistic data provided by the decision makers without any previous aggregation. Decision maker judgments are incorporated into the proposed method to generate a complete ranking of alternatives. An application in energy planning is presented as an illustrative case example in which energy policy alternatives are ranked. Seven energy alternatives under nine criteria were evaluated according to the opinion of three environmental and energy experts. The weights of the criteria are determined by fuzzy AHP, and the alternatives are ranked using qualitative TOPSIS. The proposed approach is compared with a modified fuzzy TOPSIS method, showing the advantages of the proposed approach when dealing with linguistic assessments to model uncertainty and imprecision. Although the new approach requires less cognitive effort to decision makers, it yields similar results.

The Selection of Wind Power Project Location in the Southeastern Corridor of Pakistan: A Factor Analysis, AHP, and Fuzzy-TOPSIS Application

“…The TOPSIS method was proposed by Hwang and Yoon [62]. The ambition of this technique is to identify the maximum and minimum gaps between the ideal and negative solution [63].…”

Risk-based ROI, capital budgeting, and portfolio optimization in the Department of Defense

“…To address this concern, multicriteria analysis (MCA) has become a powerful mechanism to handle multidimensional problems and to obtain an AQ supporting the final decision (Bouyssou, Marchant, Pirlot, Tsoukias, & Vincke, 2006;Brito, de Almeida, & Mota, 2010). MCA refers to a set of methods, techniques, and tools that help people with their decision problems (description, clustering, ranking, and selection) by simultaneously considering more than one objective or criterion (Afsordegan, Sánchez, Agell, Zahedi, & Cremades, 2016;Ghafghazi, Sowlati, Sokhansanj, & Melin, 2010;Kaya & Kahraman, 2011;Roy, 1996). PROMETHEE (Behzadian, Kazemzadeh, Albadvi, & Aghdasi, 2010;Brans & Mareschal, 2005;Goumas & Lygerou, 2000;Tavana, Behzadian, Pirdashti, & Pirdashti, 2013) has been proposed as a proper MCA technique.…”

Construction projects planning using network model with the fuzzy decision node

“…This choice is usually made on the basis of evaluation based on the multi-criteria analysis (Bangian et al 2012;Chernov et al 2012;Ibadov and Rosłon 2015). The evaluation criteria should refer to the essential features of a given project in a given decision situation (Ibadov 2017;Afsordegan et al 2016;Vaagen et al 2017;Narayanamoorthy and Maheswari 2017). This means that in the planning process we also have to deal with the decision-making process, which most broadly concerns: the entity, subject, period, elements and characteristics of the plan.…”