A Hybrid Genetic Algorithm to Solve Supplier Selection Problem under Stochastic Demand Condition and Quantity Discount Policy

Abstract

In this paper, we investigate a supplier selection problem composed of single manufacturer and multiple suppliers under stochastic demand condition and quantity discount policy. The objective of this problem is to select the most economical set of suppliers and to allocate the ordering quantity among the selected suppliers to minimize total costs including selection, purchase, holding and shortage costs. Since the considered problem is NP-hard, this paper presents a novel hybrid algorithm (hybrid GA_VNS) that combines genetic algorithm (GA) with variable neighborhood search (VNS) to find near optimal solutions. This algorithm merges the explorative nature of GA with the exploitative nature of VNS to enhance the effectiveness of the algorithm. The performance of the hybrid GA_VNS is verified with comparing its results with the existing GA in the literature with 60 instances.