Modeling and Optimization of Strategic Sustainable Sourcing

Abstract

Nowadays, sustainable development has received lot of attention from academic as well as from practitioners. Different industries already implemented strategies for sustainable development as it improves cooperation among companies along the supply chain to give better flow of capital, material, and information. In brief, sustainable development gives better supply chain visibility to prevent future risk or uncertainty. In this chapter, three different methods are discussed with example and case study. A two-stage sustainable supplier selection method is proposed first for multi-product assembly-to-order (ATO) production system to deal with demand uncertainty, green house gas (GHG) emission, reliability of supply, level of disassembly, and social issues of supplier selection. It is an integrated approach of intuitionistic fuzzy AHP (IF-AHP) and multi-objective genetic algorithm (MOGA). Second, a cascaded fuzzy inference system is discussed with an example. A decision support system is developed in this regard with Microsoft Visual Basic.NET (VB.NET) and MATLAB. Finally, strategic sustainable sourcing is discussed for a large number of suppliers with a case study. In the last method, “R” software and spreadsheet are used for K-means data clustering technique. In brief, an attempt has been made in this chapter to discuss several methods from sustainable sourcing to strategic sustainable procurement process.