A robust fuzzy hybrid MCDM ranking method for optimal selection of lithium extraction process from brine and seawater

Abstract

In this paper, we propose a new framework that integrates two fuzzy group decision making approaches including TOPSIS and ELECTRE II. The main objective of this combination is to improve the outcomes provided by these methods through increasing the differentiation between the alternatives in fuzzy TOPSIS and decreasing the incomparability between the alternatives in fuzzy ELECTRE. In addition, to more precisely compute the criteria weights, the correlation coefficient and standard deviation integrated model (CCSD) are used. This research has been inspired from a real case study in lithium extraction processes. Due to the quite limited mineral resources of lithium and the global efforts to replace a clean and recyclable energy instead of fossil fuels, the challenge for lithium extraction from other resources such as brines and seawater has been increased significantly. The proposed framework helps to select the most suitable process of lithium extraction from brines and seawater based on a complex multi-criteria decision making. In view of the fact that efficiency of the decision-making procedures is significantly depends on the stability of the solution, the sensitivity analysis is performed. The performance and capabilities of the proposed framework are appraised by comparing its results with some existing fuzzy MCDM methods through five lithium extraction processes from brines and seawater, as a case study. The results of the analysis indicate the rationality and enforceability of the proposed method.