B2B multi-attribute e-procurement: An artificial immune system based goal programming approach

Tung Sun Chan, M. Shukla, M. K. Tiwari, R. Shankar, King Lun Tommy Choy

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

This paper presents an artificial immune system (AIS) based goal programming approach for a multi-attribute e-procurement system. Current trends reveal that procurers are now concerned with various attributes of supplier selection, rather than negotiating only on cost. The scenario considered in this paper pertains to the procurement of an homogenous item in a large quantity. In these circumstances, procurers are forced to incorporate multi-attribute bids, dynamics pricing, related business requirements and multiple criteria in bid evaluation. The prime objective is to decide on the supplier and the quantity to be procured from the selected supplier. The problem considered here is NP hard, even without taking into account business constraints, and it becomes computationally prohibitive with an increase in the number of bids and the number of attribute values. In order to solve this problem with minimal computational time and effort, an evolutionary algorithm AIS with a goal programming technique is adopted. The working of the AIS based goal programming approach is evaluated by implementing it for a few simulated problem instances of changing complexity. The effectiveness of the proposed approach is established by a comparative study with other established evolutionary approaches such as a genetic algorithm and a simulated annealing algorithm.
Original languageEnglish
Pages (from-to)321-341
Number of pages21
JournalInternational Journal of Production Research
Volume49
Issue number2
DOIs
Publication statusPublished - 15 Jan 2011

Keywords

  • dynamic pricing
  • e-business
  • evolutionary algorithms
  • multi-attribute bids

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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