Operations Research Approach: Finding Suitable Techniques in Supply Chain Management
The Integrated Application of Effective Approaches in Supply Chain Networks
ISBN: 978-1-83549-631-2, eISBN: 978-1-83549-630-5
Publication date: 4 April 2024
Abstract
This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.
Keywords
Citation
Rostamkhani, R. and Ramayah, T. (2024), "Operations Research Approach: Finding Suitable Techniques in Supply Chain Management", The Integrated Application of Effective Approaches in Supply Chain Networks, Emerald Publishing Limited, Leeds, pp. 45-76. https://doi.org/10.1108/978-1-83549-630-520241006
Publisher
:Emerald Publishing Limited
Copyright © 2024 Ramin Rostamkhani and Thurasamy Ramayah