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A New Hybrid Algorithm to Solve Winner Determination Problem in Multiunit Double Internet Auction

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  • Mourad Ykhlef
  • Reem Alqifari

Abstract

Solving winner determination problem in multiunit double auction has become an important E-business task. The main issue in double auction is to improve the reward in order to match the ideal prices and quantity and make the best profit for sellers and buyers according to their bids and predefined quantities. There are many algorithms introduced for solving winner in multiunit double auction. Conventional algorithms can find the optimal solution but they take a long time, particularly when they are applied to large dataset. Nowadays, some evolutionary algorithms, such as particle swarm optimization and genetic algorithm, were proposed and have been applied. In order to improve the speed of evolutionary algorithms convergence, we will propose a new kind of hybrid evolutionary algorithm that combines genetic algorithm (GA) with particle swarm optimization (PSO) to solve winner determination problem in multiunit double auction; we will refer to this algorithm as AUC-GAPSO.

Suggested Citation

  • Mourad Ykhlef & Reem Alqifari, 2015. "A New Hybrid Algorithm to Solve Winner Determination Problem in Multiunit Double Internet Auction," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-10, June.
    • Handle: RePEc:hin:jnlmpe:639787
    DOI: 10.1155/2015/639787
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    Cited by:

    1. Fernanda Nakano Kazama & Aluizio Fausto Ribeiro Araujo & Paulo Barros Correia & Elaine Guerrero-Peña, 2021. "Constraint-guided evolutionary algorithm for solving the winner determination problem," Journal of Heuristics, Springer, vol. 27(6), pages 1111-1150, December.
    2. Jing Yu & Lining Xing & Xu Tan, 2021. "The new treatment mode research of hepatitis B based on ant colony algorithm," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 740-759, November.

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