A CASE STUDY ON DESIGN AND PLANNING OF MULTI-ECHELON, MULTI-COMMODITY SUPPLY CHAIN UNDER SEASONAL AND UNCERTAIN DEMAND

Abstract

Decision making is a crucial process in any business, as it adds or removes the non-value adding activities and their costs. Decision Support Systems (DSS) are developed to help the decision makers to take right decisions. DSS can be developed either by simulating or by modeling a given problem. Decisions are of three phases namely: strategic, tactical and operational level, theses decisions are made to design, plan and operate the Supply Chain respectively. Dissertation Work presented in this thesis attempts to design and plan multi-echelon, multi-commodity Supply Chain networks under seasonal and uncertain demand conditions. Work proposes two models, one for designing and other for planning the Supply Chain networks. Under designing of Supply Chain, important strategic decisions to be determined - are a) whether to open or not to open a warehouse or DC, b) transportation links and product flows between various facilities among Supply Chain and c) production rates of materials. The system is modeled mathematically as a mixed integer linear programming optimization problem. The objective of the model is to decrease infrastructure and operating costs. A case study illustrates the applicability of the model under certain and uncertain demand conditions. Under planning of Supply Chain important tactical decisions like distribution planning, production planning and setup planning have to be answered. To answer these decisions the system is modeled mathematically as a Mixed Integer Linear Programming optimization problem. Problem is modeled to decrease the non-value adding costs which incur due to seasonal demands. To see the applicability of the models, a case is considered. Both models are coded and solved in LINGO 8.0. Results are analyzed to obtain valuable managerial decisions. iii