Title: Methodology for the supplier selection and valuation problem by using a combined grouping and multi-criteria approach

Authors: Anyi Reyes; John Willmer Escobar; Julio Cesar Londoño

Addresses: Supplier Planning, Ingenio del Cauca, Cali, Valle, Colombia ' Department of Accounting and Finance, Faculty of Business Management, Universidad del Valle, Cali, Colombia ' School of Industrial Engineering, Universidad del Valle, Cali, Colombia

Abstract: The supplier selection problem (SSP) determines the choice of the best suppliers by considering qualitative and quantitative criteria. This paper proposes a two-stage hybrid methodology for selecting suppliers using the K-means grouping technique and the multi-criteria decision-making technique for order performance by similarity to ideal solution (TOPSIS). In particular, suppliers are grouped according to the K-means algorithm using diverse purchase categories of services and goods. Once the groups of suppliers with the best performance have been generated by considering several criteria, the TOPSIS algorithm establishes their ranking. The proposed approach seeks to minimise the purchase cost by selecting the suppliers with the best results under different criteria. The former methodology has been tested in a real case on a company belonging to the agro-industrial sector in Colombia. The obtained results show the efficiency of the proposed approach.

Keywords: supplier selection; k-means grouping method; MCDM; supply chain management; TOPSIS.

DOI: 10.1504/IJLSM.2023.134401

International Journal of Logistics Systems and Management, 2023 Vol.46 No.2, pp.174 - 205

Received: 22 Mar 2021
Accepted: 30 May 2021
Published online: 20 Oct 2023 *

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