Stochastic vendor selection problem: chance-constrained model and genetic algorithms

  • Shiwei He
  • Sohail S. Chaudhry
  • Zhonglin Lei
  • Wang Baohua
Article

DOI: 10.1007/s10479-008-0367-5

Cite this article as:
He, S., Chaudhry, S.S., Lei, Z. et al. Ann Oper Res (2009) 168: 169. doi:10.1007/s10479-008-0367-5

Abstract

We study a vendor selection problem in which the buyer allocates an order quantity for an item among a set of suppliers such that the required aggregate quality, service, and lead time requirements are achieved at minimum cost. Some or all of these characteristics can be stochastic and hence, we treat the aggregate quality and service as uncertain. We develop a class of special chance-constrained programming models and a genetic algorithm is designed for the vendor selection problem. The solution procedure is tested on randomly generated problems and our computational experience is reported. The results demonstrate that the suggested approach could provide managers a promising way for studying the stochastic vendor selection problem.

Keywords

Vendor selection Chance-constrained programming Stochastic Genetic algorithm 

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Shiwei He
    • 1
  • Sohail S. Chaudhry
    • 2
  • Zhonglin Lei
    • 1
  • Wang Baohua
    • 1
  1. 1.School of Traffic and TransportationBeijing Jiaotong UniversityBeijingPeople’s Republic of China
  2. 2.Department of Management and Operations/International Business, Villanova School of BusinessVillanova UniversityVillanovaUSA

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