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International Journal of Fuzzy Systems

, Volume 21, Issue 8, pp 2354–2372 | Cite as

Integrated Multi-stage Decision-Making for Winner Determination Problem in Online Multi-attribute Reverse Auctions Under Uncertainty

  • Shilei Wang
  • Shaojian QuEmail author
  • Mark Goh
  • M. I. M. Wahab
  • Huan Zhou
Article
  • 32 Downloads

Abstract

Online multi-attribute reverse auctions (OMARA), which include many non-price attributes, aligns better to practice, and is prevalent in many fields such as project bidding and public sector procurement. In such auctions, the decision makers often face varying degrees of cognitive and environmental uncertainty. This renders the traditional winner (supplier) determination method based on deterministic values impracticable. Hence, from the standpoint of the auctioneer (purchaser), a new integrated decision framework under an uncertain situation is proposed. Firstly, the fuzzy set theory is applied to the winner determination problem in OMARA to recognize the uncertainty in the bidding attribute values. Secondly, the detail description of the winner determination problem in OMARA is provided. Thirdly, the comprehensive weights of the evaluation attributes are obtained by using fuzzy AHP and fuzzy deviation maximizing method together. Lastly, the five fuzzy multi-attribute decision-making methods are combined with simple dominant principle to evaluate the bidding alternatives and determine the winner (supplier). A numerical example is used to demonstrate the process of the proposed integrated decision frame-work, and the comparative analysis illustrates its feasibility and effectiveness.

Keywords

Online multi-attribute reverse auction (OMARA) Winner determination Uncertainty Fuzzy multi-attribute decision-making methods 

Notes

Acknowledgements

This study was supported by the National Natural Science Foundation of China (No. 71571055) and Hujiang Leading Talent Project of Shanghai (101730301725). We gratefully acknowledge the anonymous referees for their valuable comments and suggestions.

Compliance with Ethical Standards

Conflict of interest

The authors declare that that they have no conflicts of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Taiwan Fuzzy Systems Association 2019

Authors and Affiliations

  • Shilei Wang
    • 1
  • Shaojian Qu
    • 1
    Email author
  • Mark Goh
    • 2
  • M. I. M. Wahab
    • 3
  • Huan Zhou
    • 1
  1. 1.Business SchoolUniversity of Shanghai for Science and TechnologyShanghaiPeople’s Republic of China
  2. 2.NUS Business School & The Logistics Institute-Asia PacificNational University of SingaporeSingaporeSingapore
  3. 3.Department of Mechanical and Industrial EngineeringRyerson UniversityTorontoCanada

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