Supply chain management under uncertainty with the combination of fuzzy multi-objective planning and real options approaches

The concentration of this paper is to measure and break supply chain planning decisions under market and/or technical uncertainty. A three-level supply chain with manufacturers–distributors–customer’s loops is considered that customer demands, percent of back products from customers and shipping time of products from distributors to customers are considered as fuzzy variables. The main approach considers suppliers and distributor selection and determines the affected customers in the system problems simultaneously under uncertain conditions. The objects of the proposed model are maximizing the quality of products and income and minimizing the total cost and the shipping time from distributors to customers. Also, in the proposed model we consider some constraints such as lack of orders, production capacity and customer demands. Also, a two-organize, stochastic programming methodology is proposed for joining request vulnerability in multisite midterm store network arranging issues. The assessment of the normal second-stage expenses is accomplished by expository reconciliation yielding an equivalent convex mixed-integer nonlinear problem. At long last, a real options-based valuation (ROV) system for supporting under vulnerability is produced. Multistage stochastic writing computer programs are utilized to fuse vulnerability and a quantitative correlation of the ROV approach, and the customary net-present-value approach is given.