Rose Wine industry of Supply Chain Management for Storage using Genetic Algorithm

Abstract

Managing the supply chain of the rose wine sector for environmental cooperation and sustainability through Genetic algorithm is an integral part of the management of stocks in the rose wine sector. The new competent approach requires Genetic algorithm to optimize stocks in the rose wine industry for supply chain management for environmental collaboration. We also focus on the complexity of predicting optimal stocks and congestion levels to optimize stocks in the rose wine sector, from supply chain management to environmental cooperation to keep the total cost of managing the supply chain inventory for the rose wine industry. We use our methods in the rose wine industry in supply chain management for an optimization model studied in environmental cooperation. The proposed method was implemented and its performance was evaluated by MATLAB.