A hybrid model for suppliers' selection based on clustering method using NRGA and NSGA-II algorithms

Abstract

Supply chain management (SCM) is one of the most important competitive strategies used by modern companies. The main goal of supply chain management is integration different suppliers to fulfill market demand. Therefore, evaluation and selection of suppliers has critical role and significant effect on supply chain management. This paper presents hybrid model based on clustering approach and suppliers' selection. At first, K-harmonic means clustering method which is one of the most popular methods in clustering analysis is used for clustering suppliers. Then, according to theoutput of clustering, a multi-objective model is considered to select the best supplier. Since the model belongs to the class of NP-hard optimization problems, two meta-heuristic algorithms named Non-dominated Sorting Genetic Algorithm (NSGAII) and Non-dominated Ranked Genetic Algorithm (NRGA) is used for solving model in reasonable time. Computational results show that the clustering analysis can be considered as an effective way to the suppliers' selection. Also, several data sets are applied to evaluate the effect of clustering analysis on suppliers' selection

Keywords

• supplier selection
• supply chain management
• supplier clustering
• k-harmonic means assistant