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Approaches for multi-attribute auctions

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2009
Karakaya, Gülşah
There is a growing interest in electronic auctions in the literature. Many researchers work on the single attribute version of the problem. Multi-attribute version of the problem is more realistic. However, this brings a substantial difficulty in solving the problem. In order to overcome the computational difficulties, we develop an Evolutionary Algorithm (EA) for the case of multi-attribute multi-item reverse auctions. We generate the whole Pareto front using the EA. We also develop heuristic procedures to find several good initial solutions and insert those in the initial population of the EA. We test the EA on a number of randomly generated problems and compare the results with the true Pareto optimal front obtained by solving a series of integer programs. We also develop an exact interactive approach that provides aid both to the buyer and the sellers for a multi-attribute single item multi round reverse auction. The buyer decides on the provisional winner at each round. Then the approach provides support in terms of all attributes to each seller to be competitive in the next round of the auction.