Production planning under demand uncertainty using Monte Carlo simulation approach: a case study in fertilizer industry

Abstract

Production planning as a strategic decision involves the allocation of aggregate production resources for groups of aggregate products. Is performed in a manufacturing setting to provide efficient utilization of those production resources while meeting sales opportunities for the finished products. In this paper the production planning is studied under demand uncertainty. The consideration of uncertainty in manufacturing systems requires consideration not only of demand but also of alternative scenarios of variations in these demands. The aim of this study is to evaluate the robustness of a system consists of satisfying the total demand in a multi-facility plant forming a production-inventory network. To consider the demand uncertainty, a set of possible scenarios for demands is created based on the Monte Carlo simulation. The deterministic model takes the form of a Mixed Integer Linear Program (MILP) which objective is to maximize the customer demand satisfaction (CDS) level. The proposed model provides an effective tool for evaluating the exposure of a firm assets to market uncertainties. The key features of the integrated model is illustrated with a case study of fertilizers production industry.