IMPROVING QUALITY AND REDUCING COSTS IN SUPPLY CHAIN: THE DEVELOPING VIKOR METHOD AND OPTIMIZATION

Abstract

In today’s competitive world, the quality of raw material plays a significant role in the success of organizations. Since the quality of raw materials is a factor that leads to a reduction in return products, the selection of raw material supplier’s problem has always been daunting challenges in supply chain. The supplier’s selection problem is a multi-criteria group decision-making (MCGDM) that the preferences over criteria, and suppliers are highly dependent on the opinions of experts. In the real world, decisionmakers cannot express their opinions with certainty. In this study, a novel hesitant fuzzy linguistic Term set Vlsekriterijumska Optimizacija I Kompromisno Resenje (HFLTs-VIKOR) approach is proposed for solving supplier selection problems with hesitant fuzzy linguistic set information. In this regard, a new context-free grammar has been proposed. In the present study, the quality of raw materials due to their impact on environmental issues and the amount of product waste has been investigated using the proposed method. Then, using a designed model, an appropriate ordering policy is identified to minimize costs and maximize the value of suppliers at supply chain, production, and distribution levels. Finally, the efficiency of the presented method is verified through a case study with real data.