Analytic Hierarchy Process (AHP) and Goal Programming Approach for a Real-Life Supplier Selection Problem

Abstract

In today’s intricate and competitive business environment the selection of suppliers plays a pivotal role in determining the success and efficiency of a company’s operations. Supplier selection is a multifaceted decision-making process that involves evaluating and comparing various factors such as quality cost lead time and reliability. To address the complexities inherent in this process organizations turn to advanced decision support methodologies. This study delves into a real-life supplier selection problem and explores the application of two prominent decision-making approaches: the Analytic Hierarchy Process (AHP) and Goal Programming. AHP provides a structured framework for systematically analysing complex decision criteria and preferences while Goal Programming facilitates the optimization of multiple conflicting objectives. The objective is the integration of AHP and Goal Programming to offer decision-makers a robust framework for analysing prioritizing and optimizing complex supplier selection problems. Effective supplier evaluation is crucial for the success of garment manufacturing facilities as it impacts the quality cost and timely delivery of raw materials and supplies required for production. AHP provides a structured approach to decision-making by breaking down complex decisions into a hierarchy of criteria and alternatives and enabling decision-makers to assign weights to each criterion based on their relative importance. Goal Programming on the other hand is a mathematical programming technique that helps decision-makers to find the best possible solution that satisfies multiple often conflicting objectives. This integration enables them to achieve a balanced and well-informed decision-making process aligned with the strategic goals and objectives of the organization. The combination of AHP and Goal Programming can provide a powerful decision-making framework for evaluating suppliers in garment manufacturing facilities. © 2024 Elsevier B.V. All rights reserved.