Abstract
The problem of energy crisis and environmental pollution has been mitigated by the generation and use of wind power; however, the choice of locations for wind power plants is a difficult task because the decision-making process includes political, socioeconomic, and environmental aspects. Thus, several adverse consequences have been created by the choice of suboptimal locations. The objective of this paper is to address the integrated qualitative and quantitative multicriteria decision-making framework for the selection of wind power plant locations. Spherical fuzzy sets are the latest extension of the ordinary fuzzy sets. The main characteristic of the spherical fuzzy sets is satisfying the condition that the squared sum of the positive, neutral, and negative grades must be at least zero and at most one. In this research, we establish novel operational laws based on the Yager t-norm and t-conorm under spherical fuzzy environments (SFE). Furthermore, based on these Yager operational laws, we develop list of novel aggregation operators under SFE. In addition, we design an algorithm to tackle the uncertainty to investigating the best wind power plant selection in four potential locations in Pakistan. A numerical example of wind power plant location problem is considered to show the supremacy and effectiveness of the proposed study. Also, a detailed comparison is constructed to evaluate the performance and validity of the established technique.
Highlights
One of the common and daily activity in humans’ life is decision-making, aiming to choose the optimal alternative with respect to a list of attributes
Due to the uncertainty of decision information, utilizing fuzzy set theory to settle decision-making problem has become a hotspot in recent years. e concept of fuzzy set (FS) theory was firstly proposed by Zadeh [1], and, since the FSs have been widely used in many decision-making (DM) problems
From the outcomes of the proposed operators and the other existing methods, we conclude that ranking lists obtained from both the proposed method and the compared methods are the same. e Yager operators with the spherical fuzzy set environment represent a generalized and novel approach to tackle uncertainty in DM problems. e Yager operators with the spherical fuzzy environment are more flexible and effective to evaluate best alternative in real-word problems
Summary
One of the common and daily activity in humans’ life is decision-making, aiming to choose the optimal alternative with respect to a list of attributes. Many researchers contribute to intuitionistic FS theory; for example, Xu and Yager [8] introduced the geometric means-based aggregation operators (AOs) under intuitionistic FSs. Xu [9] established list of novel AOs to tackle the complex uncertainty under intuitionistic fuzzy settings. Erefore, in this article, our aim is to present some novel spherical fuzzy Yager operational laws based AOs to tackle the uncertainty in real-world DM problems with more effective and efficient way. (i) Novel ranking methodology and Yager norm-based novel operational laws for spherical fuzzy sets are proposed (ii) e new spherical fuzzy Yager averaging/geometric aggregation operators are proposed to aggregate the uncertainties in the form of spherical fuzzy environment (iii) Decision-making algorithm is proposed to tackle the real-world DM problems (iv) A real-life numerical application about wind power plant location selection problem in Pakistan is discussed to show the applicability of the proposed technique e rest of this article shall be organized as set out below.
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