An Integrated EDAS-ELECTRE Method With Picture Fuzzy Information for Cleaner Production Evaluation in Gold Mines

Abstract

Faced with the contradiction between economic growth and environmental pollution, implementing cleaner production has become a good choice for many mining companies to achieve sustainable development. This paper aims to evaluate the cleaner production for gold mines by exploring applicable decision making methods. First, the picture fuzzy numbers with four membership degrees are adopted to describe experts’ assessment information under complicated fuzzy environment. Thereafter, the extended stepwise weight assessment ratio analysis and mean-squared deviation models are combined to obtain the comprehensive criteria weights. Meanwhile, a novel evaluation method, which integrates the evaluation based on distance from average solution (EDAS) with elimination and choice translating reality (ELECTRE) module, is proposed to judge the cleaner production level. Subsequently, according to the characteristics of gold mines, an evaluation criteria system of cleaner production is constructed. Finally, a case of evaluating the cleaner production performance for four gold mines is provided to explain the application of the proposed method. Besides, a systematic comparison analysis with other existent methods is conducted to reveal the advantages of our method. Results indicate that the integrated EDAS-ELECTRE method is suitable and effective for gold mines to evaluate their cleaner production performance, and has important reference values for the cleaner production management and implementation.

Keywords

• Cleaner production evaluation
• combined weights
• EDAS (evaluation based on distance from average solution) approach
• ELECTRE (elimination and choice translating reality) approach
• PFNs (picture fuzzy numbers)