Green Manufacturing Based on DE Algorithm in Probabilistic Language Environment Supply and Demand in the Supply Chain Matching Decision Methods

Abstract

With the strategy of "green manufacturing", it is especially important to develop from traditional manufacturing to low-carbon, low-cost, and environmentally friendly manufacturing with high quality and efficiency. Supply and demand matching in the supply chain is considered to be an effective way to improve the efficiency of manufacturing management. In dealing with the green supply chain supply and demand matching problem in a probabilistic language environment, this study proposes a decision-making method based on a differential evolution (DE) algorithm. By adopting a probabilistic language term set to express the supply and demand information structure of the supply chain, designs the corresponding utility function accordingly; Secondly, this paper establishes a bilateral matching model for the characteristics of the matching satisfaction, and solves the optimal matching solution through the evolutionary algorithm; Lastly, through the specific case, this study confirms that the method is effective.