Supply chain planning using multi-stage stochastic programming

Purpose - The purpose of this paper is to explore the functionality of multistage programming approach on network supply chain structure. Design/methodology/approach - The general supply chain structure is considered and the supply chain planning model is developed using a two stage programming approach. The same model is extended to cover the applicability and advantages of a multi-stage programming approach. Findings - A multi-period supply chain model for new product launches under uncertain demand for supply chain network structure has been developed. The model allows simultaneous determination of optimum procurement quantity production quantity across the different plants, transportation routes and the outsourcing cost in case of shortages. The proposed multi-stage model is compared with the standard two-stage model by examining the difference between the objective values of two solutions. The research clearly shows the importance of the multi-stage model as compared to the two-stage programming model. Research limitations/implications - The models developed here are limited to covering demand uncertainty whereas real supply chain exhibits different uncertainties like capacity, processing time, etc. This can be the future direction for extending the work. Practical implications - The model is very useful in designing and planning the supply chain in an uncertain environment. The model allows the adjustment of the production plan as time progresses and uncertainties become resolved. Originality/value - The model uses a scenario approach to address the supply chain planning problem for a supply chain network structure under an uncertain environment and compares the two-solution approach for a set of problems. Generally supply chain costs are in millions of dollars and the saving using multi-stage programming can be significant.