Supply Chain Management Optimization and Prediction Model Based on Projected Stochastic Gradient

Supply chain management (SCM) is considered at the forefront of many organizations in delivery their products. Various optimization methods are applied SCM to improve efficiency process. In this research, projected stochastic gradient (PSG) method was proposed increase analysis. The key objective an efficient supply find best flow patterns for products order select suppliers different customers. Hence, focus research on developing multi-echelon using factors such as cost, time, and risk. convex case, has advantage a weakly convergent sequence iterates point set minimizers with probability one. developed achieves strong convergence unique optimum, dataset utilized assess method’s performance. PSG considering holding cost profit analysis company. results analyzed according product’s profit, stock, demand. also provides prediction demand profit.