Winner determination problem with loss-averse buyers in reverse auctions

Abstract

Reverse auctions have been widely adopted for purchasing goods and services. This paper considers a novel winner determination problem in a multiple-object reverse auction in which the buyer involves loss-averse behavior due to uncertain attributes. A corresponding winner determination model based on cumulative prospect theory is proposed. Due to the NP-hard characteristic, a loaded route strategy is proposed to ensure the feasibility of the model. Then, an improved ant colony algorithm that consists of a dynamic transition strategy and a Max-Min pheromone strategy is designed. Numerical experiments are conducted to illustrate the effectiveness of the proposed model and algorithm. We find that under the loaded route strategy, the improved ant colony algorithm performs better than the basic ant colony algorithm. In addition, the proposed model can effectively characterize the buyer’s loss-averse behavior.

Keywords

reverse auction / loss aversion / winner determination / improved ant colony algorithm

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Acknowledgements

This work has been sponsored by the Distinguished Young Scholars Award of NSFC Grant #71325002; the Major International Joint Research Project of NSFC Grant #71620107003; the Foundation for Innovative Research Groups of NSFC Grant #61621004; 111 Project Grant #B16009; and the Fundamental Research Funds for State Key Laboratory of Synthetical Automation for Process Industries Grant #2013ZCX11.

RIGHTS & PERMISSIONS

2017 The Author(s) 2017. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)