Research Output

A Cooperative Learning Approach for the Quadratic Knapsack Problem

  The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has several applications in different fields such as telecommunications, graph theory, logistics, hydrology and data allocation, among others. In this short paper, we propose the application of a novel population-based metaheuristic, which exploits the concepts of cooperation and communication along the search leading to a collective learning, to solve a wide range of well-known QKP instances.

  • Date:

    31 December 2018

  • Publication Status:

    Published

  • DOI:

    10.1007/978-3-030-05348-2_3

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    004 Data processing & computer science

  • Funders:

    Edinburgh Napier Funded

Citation

Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018). A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12). , (31-35). https://doi.org/10.1007/978-3-030-05348-2_3

Authors

Keywords

Optimization problem, linear capacity, novel population-based metaheuristic,

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    A Cooperative Learning Approach for the Quadratic Knapsack Problem

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    This is a post-peer-review, pre-copyedit version of an article published in Learning and Intelligent Optimization
    12th International Conference, LION 12, Kalamata, Greece, June 10–15, 2018, Revised Selected Papers. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-05348-2_3.

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