A HYBRID GENETIC ALGORITHM TO SOLVE SUPPLIER SELECTION PROBLEM UNDER STOCHASTIC DEMAND CONDITION AND QUANTITY DISCOUNT POLICY

摘要：

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.

关键词： Supplier selection Genetic algorithm Variable neighborhood search stochastic demand Discount price

作者: AZIZOLLAH JAFARI SEYEDEH MARZIEH BANIHASHEMITEHRANI PAYAM CHINIFOROOSHAN

作者单位: Department of Industrial Engineering,University of Science and Culture,Tehran,Iran

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 389-394

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）