A Piecewise Objective Probabilistic Optimization Approach as Decision Making for Supplier Selection and Inventory Management With Price Discount

Abstract

A mathematical model in the form of a piecewise objective probabilistic optimization approach was proposed in this study as the new decision-making tool to solve supplier selection and inventory management problems. The focus was on price discount and uncertain parameters such as product demand, product defect rate, and late-delivery product rate, which were approached using random variables with some known probability distribution function. Meanwhile, the decision variables contained in the model include the product volume ordered by each supplier at each time for each product type and those stored in the inventory to minimize the total operational cost in the problem. The corresponding optimization problem was solved using a probabilistic programming algorithm via the LINGO optimization tool. The computational simulation showed the proposed model provided the optimal decision, and this means it can be used as a decision-making tool by industrial practitioners.