Abstract
Winner determination in combinatorial reverse auctions is very important in e-commerce especially when multiple instances of items are considered. However, this is a very challenging problem in terms of processing time and quality of the solution returned. In this paper, we tackle this problem using genetic algorithms. Using a modification of the crossover operator as well as two routines for consistency checking, our proposed method is capable of finding the winner(s) with a minimum procurement cost and in an efficient processing time. In order to assess the performance of our GA-based method, we conducted several experiments on generated instances. The results clearly demonstrate the good time performance of our method as well as the quality of the solution returned.
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Shil, S.K., Mouhoub, M. (2014). Considering Multiple Instances of Items in Combinatorial Reverse Auctions. In: Ali, M., Pan, JS., Chen, SM., Horng, MF. (eds) Modern Advances in Applied Intelligence. IEA/AIE 2014. Lecture Notes in Computer Science(), vol 8482. Springer, Cham. https://doi.org/10.1007/978-3-319-07467-2_51
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DOI: https://doi.org/10.1007/978-3-319-07467-2_51
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