Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3655
Title: Reverse Ant Colony Optimization for the Winner Determination Problem in Combinatorial Auctions
Authors: Uzunbayır, Serhat
Keywords: ant colony optimization
combinatorial auctions
meta-heuristics
winner determination problem
Artificial intelligence
Commerce
Genetic algorithms
Polynomial approximation
Ant Colony Optimization algorithms
Combinatorial auction
Different sizes
Efficient allocations
Metaheuristic
Minimisation
NP Complete
Paper reverse
Polynomial-time
Winner determination problem
Ant colony optimization
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: An auction is an effective process of trading items among bidders and sellers. Combinatorial auctions are auctions in which bidders can place bids on a bundle of items rather than bidding on a single item. As a result, they lead to more efficient allocations compared to traditional auctions. Determining the winners whose bids maximize the auctioneer's profit is known as the winner determination problem. The problem is NP-complete since it is not possible to solve it in polynomial time as the inputs increase. In this paper, reverse ant colony optimization algorithm is proposed for the problem which focuses on maximization of the ants' route instead of minimization of the regular version. The experimental results are compared using different size data sets with a previously proposed genetic algorithm and a random search algorithm. The experiments indicate that, as the search space expands, the proposed algorithm finds better solutions than the others. © 2022 IEEE.
Description: 7th International Conference on Computer Science and Engineering, UBMK 2022 -- 14 September 2022 through 16 September 2022 -- 183844
URI: https://doi.org/10.1109/UBMK55850.2022.9919488
https://hdl.handle.net/20.500.14365/3655
ISBN: 9.78167E+12
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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