A genetic approach to the quadratic assignment problem
Computers and Operations Research - Special issue on genetic algorithms
Solving Combinatorial Auctions Using Stochastic Local Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
GA Based Winner Determination in Combinatorial Reverse Auction
EAIT '11 Proceedings of the 2011 Second International Conference on Emerging Applications of Information Technology
An efficient hierarchical parallel genetic algorithm for graph coloring problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Nowadays, winner determination problem is one of the main challenges in the domain of real-time applications such as combinatorial reverse auctions. To determine the winner(s) in combinatorial reverse auctions, in our previous work, we have proposed a Genetic Algorithm (GA)-based method and have demonstrated its superiority in terms of processing time and procurement cost. One of the main drawbacks of traditional GA-based solutions is their inconsistency in different runs. In this paper, we perform a statistical-based experiment that reveals that our proposed method is not affected by the inconsistency issue. In addition, we show two other features of our GA-based method: (1) the quality of the solution improves over generations, and (2) the any-time behavior.