Linguistic neutrosophic Hamacher aggregation operators and the application in evaluating land reclamation schemes for mines

Comprehensive evaluation of land reclamation schemes in mining areas based on linguistic intuitionistic fuzzy group decision-making

Schemes to protect the geological environment and reclaim land are core requirements for an application for mining rights and complying with mining regulations. Mining enterprises must be supervised to ensure they fulfill their obligations. To guide oversight of such schemes and to provide references for their compilation and review, this study evaluates land reclamation schemes in mining areas using a multi-attribute group decision-making method. First, linguistic intuitionistic fuzzy numbers are used to describe the evaluation information. Considering the authority and preferences of experts, methods for determining expert weights in four cases are established. Max-min deviation then determines the attribute weights, and a method for linguistic intuitionistic fuzzy group decision-making is proposed. Finally, the practicability of this method is verified through a comparative analysis of land reclamation schemes for four mining areas in Sichuan Province, China. The results show the proposed method to give simple and effective evaluation, making it reasonably applicable to the compilation and review of land reclamation schemes.

A new multi-criteria decision-making method utilizing power heronian operators with picture hesitant fuzzy information

In practice, picture hesitant fuzzy sets (PHFSs) combining the picture fuzzy sets (PFSs) and hesitant fuzzy sets (HFSs) are suitable to represent more complex multi-criteria decision-making (MCDM) information. The power heronian (PH) operators, which have the merits of power average (PA) and heronian mean (HM) operators, are extended to the environment of PHFSs in this article. First, some algebraic operations of picture hesitant fuzzy numbers (PHFNs), comparative functions and distance measure are introduced. Second, two novel operators, called as picture hesitant fuzzy weighted power heronian (PHFWPH) operator and picture hesitant fuzzy weighted geometric power heronian (PHFWGPH) operator, are defined. Meanwhile, some desirable characteristics and special instances of two operators are investigated as well. Third, a novel MCDM approach applying the proposed PH operators to handle PHFNs is explored. Lastly, to indicate the effectiveness of this novel method, an example regarding MCDM problem is conducted, as well as sensitivity and comparison analysis.

Hamacher heronian mean operators for multi-critria decision-making under multi-valued picture fuzzy uncertain lingsuitic environment

Picture fuzzy set (PFS) and linguistic term set (LTS) are two significant notions in multi-criteria decision-making (MCDM). In practice, decision-makers sometimes need utilize the multiple probable membership degrees for an uncertain linguistic term to express evaluation information. Motivated by these, to better convey the vagueness and uncertainty of cognitive information, multi-valued picture fuzzy uncertain linguistic set combining picture hesitant fuzzy set with uncertain linguistic term set is proposed. We firstly define the concepts of multi-valued picture fuzzy uncertain linguistic set and multi-valued picture fuzzy uncertain linguistic number. Hamacher operations are more general and flexible in information fusion, thus, Hamacher operations and comparison method are developed at the same time. Improved generalized Heronian Mean operator can simultaneously reflect correlations between values and prevent the redundant calculation. Then, two operators of improved generalized weighted Heronian mean and improved generalized geometric weighted Heronian mean in view of Hamacher operations are proposed. Meanwhile, some distinguished properties and instances of two operators are explored as well. Moreover, a novel MCDM approach applying the developed operators is constructed. Ultimately, an illustrative example on vendor selection is performed, and sensitivity analysis and comparison analysis are provided to verify the powerfulness of the proposed method.

Entropy-Based GLDS Method for Social Capital Selection of a PPP Project with q-Rung Orthopair Fuzzy Information

The social capital selection of a public–private-partnership (PPP) project could be regarded as a classical multiple attribute group decision-making (MAGDM) issue. In this paper, based on the traditional gained and lost dominance score (GLDS) method, the q-rung orthopair fuzzy entropy-based GLDS method was used to solve MAGDM problems. First, some basic theories related to the q-rung orthopair fuzzy sets (q-ROFSs) are briefly reviewed. Then, to fuse the q-rung orthopair fuzzy information effectively, the q-rung orthopair fuzzy Hamacher weighting average (q-ROFHWA) operator and q-rung orthopair fuzzy Hamacher weighting geometric (q-ROFHWG) operator based on the Hamacher operation laws are proposed. Moreover, to determine the attribute weights, the q-rung orthopair fuzzy entropy (q-ROFE) is proposed and some significant merits of it are discussed. Next, based on the q-ROFHWA operator, q-ROFE, and the traditional GLDS method, a MAGDM model with q-rung orthopair fuzzy information is built. In the end, a numerical example for social capital selection of PPP projects is provided to testify the proposed method and deliver a comparative analysis.

Linguistic neutrosophic power Muirhead mean operators for safety evaluation of mines

Safety is the fundamental guarantee for the sustainable development of mining enterprises. As the safety evaluation of mines is a complex system engineering project, consistent and inconsistent, even hesitant evaluation information may be contained simultaneously. Linguistic neutrosophic numbers (LNNs), as the extensions of linguistic terms, are effective means to entirely and qualitatively convey such evaluation information with three independent linguistic membership functions. The aim of our work is to investigate several mean operators so that the safety evaluation issues of mines are addressed under linguistic neutrosophic environment. During the safety evaluation process of mines, many influence factors should be considered, and some of them may interact with each other. To this end, the Muirhead mean (MM) operators are adopted as they are powerful tools to deal with such situation. On the other hand, to diminish the impacts of irrational data provided by evaluators, the power average (PA) operators are under consideration. Thus, with the combination of MM and PA, the power MM operators and weighted power MM operators are proposed to aggregate linguistic neutrosophic information. Meanwhile, some key points and special cases are studied. The advantages of these operators are that not only the interrelations among any number of inputs can be reflected, but also the effects of unreasonable information can be reduced. Thereafter, a new linguistic neutrosophic ranking technique based on these operators is developed to evaluate the mine safety. Moreover, in-depth discussions are made to show the robust and flexible abilities of our method. Results manifest that the proposed method is successful in dealing with mine safety evaluation issues within linguistic neutrosophic circumstances.

Evaluation of Cleaner Production for Gold Mines Employing a Hybrid Multi-Criteria Decision Making Approach

Implementing cleaner production (CP) is effective to resolve the contradiction between economic growth and environmental crisis. To avoid destroying the ecological environment in the exploitation process of mineral resources, CP has been developed in many gold mines to achieve the goal of sustainable development. Thus, this paper aims to propose a favorable approach to assess CP for gold mines. First, according to the specific characteristics of gold mines, an evaluation criteria system of CP is established. Meanwhile, considering the diversity of evaluation information, crisp numbers and probabilistic linguistic term sets (PLTSs) are adopted to indicate the quantitative and qualitative information, respectively. Subsequently, a modified experts grading method based on PLTSs is proposed to calculate the sub-criteria weights’ values. Following this, an extended Tomada de Decisão Interativa Multicritério (TODIM) method with hybrid evaluation values is presented to obtain the ranking order. Finally, the hybrid multi-criteria decision making (MCDM) approach is applied to a case of assessing CP for gold mines to demonstrate its feasibility. Furthermore, the robustness and advantages of this approach are justified by sensitivity and comparison analyses. The results show that the proposed approach is feasible to solve such kinds of evaluation problems with hybrid decision making information and can provide some managerial suggestions for government and enterprises.