An improved ant colony algorithm for winner determination in multi-attribute combinatorial reverse auction

This paper considers the problem of one buyer procuring multi-items from multiple potential suppliers in the electronic reverse auction, where each supplier can bid on combinations of items. From the perspective of the buyer, by considering multi-attributes of each item, a winner determination problem (WDP) of multi-items single-unit combinatorial reverse auctions was described and a bi-objective programming model was established. According to the characteristics of the model, an equivalent single-objective programming model was obtained. As the problem is NP-hard, an improved ant colony (IAC) algorithm considering the dynamic transition strategy and the Max-Min pheromone strategy is proposed for the problem. Experimental results show the effectiveness of the improved algorithm.