Adaptative Strategies for Multicriteria Auctions : an Empirical Study
Brigui-Chtioui, Imène; Caillou, Philippe; Pinson, Suzanne (2022), Adaptative Strategies for Multicriteria Auctions : an Empirical Study, in Lalit Garg, Dilip Singh Sisodia, Nishtha Kesswani, Joseph G Vella, Imene Brigui, Peter Xuereb, Sanjay Misra, Deepak Singh, Information Systems and Management Science, Springer : Berlin Heidelberg, p. 174–184. 10.1007/978-3-031-13150-9_16
TypeCommunication / Conférence
Conference title4th International Conference on Information Systems and Management Science (ISMS) 2021
Book titleInformation Systems and Management Science
Book authorLalit Garg, Dilip Singh Sisodia, Nishtha Kesswani, Joseph G Vella, Imene Brigui, Peter Xuereb, Sanjay Misra, Deepak Singh
Number of pages580
MetadataShow full item record
emlyon business school [EM]
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)Book coverInternational Conference on Information Systems and Management ScienceISMS 2021: Information Systems and Management Science pp 174–184Cite asAdaptive Strategies for Multicriteria Auctions: An Empirical StudyImène Brigui, Philippe Caillou & Suzanne Pinson Conference paperFirst Online: 29 November 202247 AccessesPart of the Lecture Notes in Networks and Systems book series (LNNS,volume 521)AbstractIn this paper, we propose bidding strategies for conducting automated reverse auctions based on a non-compensatory multicriteria model. We conduct an empirical multiagent study in order to appreciate the relevance of the proposed strategies. In this type of auction and in order to ensure ascending process evolution, the design of such automated systems often uses a fixed bid increment representing the minimum amount by which a bidder must improve on the current best bid. This article suggests adjusting the bid increment as the auction process goes on. To this end, we propose buyer counterproposal which ensures an acceptable solution at any given time. To this end, we refer to the auction context based on the number of remaining suppliers or the remaining time at each process step. We also present and demonstrate some interesting properties of the proposed algorithm. Finally, we provide an empirical study that compares a fixed-increment strategy to our proposed strategies on the basis of a variation of different auction settings.
Subjects / KeywordsDecision models; Automated auctions; Multiagent systems; Bidding strategies
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