A fuzzy hybrid approach for supplier selection and order allocation

Subject Areas : Environmental Toxicology

Reyhaneh Hajati ¹ , Majid Nojavan ² , Davood Mohammaditabar ³

1 - M.Sc,, Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Assistant Professor, Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran (Correspondence Officer)
3 - Assistant Professor, Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

Received: 2019-09-01 Accepted : 2019-12-25 Published : 2020-02-20

Keywords: Fuzzy Inference, Supplier Selection and Order Allocation, Fuzzy DEMATEL-ANP, Fuzzy WASPAS, Multi-Objective Mixed Integer Programming,

Abstract :

In this paper, a new hybrid approach in supplier selection and order allocation is proposed. At the first step, the supplier evaluating criteria and sub-criteria are determined and their relationships and degrees of importance are specified via the fuzzy ANP-DEMATEL method. Afterwards, regarding the high variety of purchasing items, they are categorized into four groups by the Fuzzy Inference system (Kraljik model) and suppliers in each group are ranked using the Fuzzy WASPAS method. The next step is to determine the order allocation of items in a multi-product, multi-period, multi-supplier mixed integer programming model with three objectives of minimizing the cost, maximizing total utility of the purchasing process and minimizing changes of selected suppliers as a new objective function. Finally, the LP metric method is applied to solve the proposed multi-objective model, and Pareto solutions of the problem are determined by changing the coefficients of the objectives in this method. The proposed approach is used for suppliers evaluation and order allocation in a chemical company with a high number of purchasing items and suppliers. The accuracy of results is confirmed by experts. Regarding the comprehensiveness of the proposed approach, its application increases the accuracy of suppliers evaluation and order allocation, and therefore its utilization in organizations is recommended.