面向电子逆向拍卖的多属性报价建议模型

摘要

针对多属性拍卖中报价的复杂性和现有报价指导模型的局限性,提出了一个以拍卖方的总价值提升为基本约束,以投标人的利润最大化为目标的多属性报价建议模型,并引入二元变量解决了定性属性的推荐问题.当投标人具有不同的投标能力和偏好时,模型可根据投标人的投标要求进行报价推荐;当存在单位价值相同的推荐报价时,模型设置了相应的约束以鼓励早投标行为.最后,还从理论上证明了该模型的稳定性,并通过算例说明了模型的可行性.%Considering the complexity of bidding in multi-attribute auctions and the limitations of existing models, a multi-attribute bids suggestion model is proposed. Under the basic constraint that the auctioneer' s total value should be increased in every iteration, the model maximizes profit of the bidder who asks for bids, and recommends values for qualitative attributes by introducing a set of binary variables. Allowing for different bidding capabilities and different preferences of the bidders, the model could suggest for bids according to their bidding requirements. Besides, in case there are several bids with the same value, the model could encourage early bidding behavior via respective constraints. Finally, theoretical analysis confirms the stability of the model, and an application example validates its feasibility.