A Study of Supply Chain Management System Using Optimization Techniques

Abstract

In this thesis, we advance Supply Chain Management (SCM) by introducing a deterministic model that integrates opportunity costs to ensure efficient operations across suppliers, manufacturers and warehouses. To address uncertainties in cost and demand, we propose a fuzzy mathematical programming model using the and#945;-cut approach, alongside robust decision-making methods such as Fuzzy AHP, SWARA and TOPSIS. An illustrative example demonstrates the versatility of these models for optimizing both small and large-scale industries. The conclusion of this thesis as follows: newline In Chapter 2 Optimization model is developed by using Linear Programming problem (LPP) for Multi-Echelon and Multimodal supply chain system considering opportunity cost in order to configure the network to minimize total cost. Total cost includes shipping cost from supplier to plant, transportation cost between plants and distribution centre, distribution cost between distribution centre and customer zones and opportunity cost associated with untimely material availability. At the last an Industrial case study is used to demonstrate the feasibility of applying general Linear Programming Model which results in total cost reduction of supply chain network. This method serves as a straightforward and efficient approach to obtaining optimal solutions for multi-echelon supply chain networks. The proposed model is versatile and applicable to both small-scale and large-scale industries. newline newline