Showing 81 - 100 results of 1,632 for search '"Combinatorial optimization"', query time: 0.53s Refine Results
  1. 81

    Using data-mining techniques to improve combinatorial optimization algorithms by Peter Jamieson, Farnaz Gharibian, Lesley Shannon, Steve Wilton

    Published 2022-10-01
    “…In this work, we show how data-mining can be used to cluster algorithmic generated data and use that data to improve algorithms that solve combinatorial optimization problems for a real-world application—the field-programmable gate array placement problem. …”
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    A combinatorial optimization approach for diverse motif finding applications by Singh Mona, Zaslavsky Elena

    Published 2006-08-01
    “…</p> <p>Results</p> <p>We introduce a versatile combinatorial optimization framework for motif finding that couples graph pruning techniques with a novel integer linear programming formulation. …”
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    Article
  6. 86

    Robust combinatorial optimization under convex and discrete cost uncertainty by Christoph Buchheim, Jannis Kurtz

    Published 2018-09-01
    “…In this survey, we discuss the state of the art of robust combinatorial optimization under uncertain cost functions. We summarize complexity results presented in the literature for various underlying problems, with the aim of pointing out the connections between the different results and approaches, and with a special emphasis on the role of the chosen uncertainty sets. …”
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    Reinforcement learning enhanced quantum-inspired algorithm for combinatorial optimization by Beloborodov, D, Ulanov, AE, Foerster, JN, Whiteson, S, Lvovsky, AI

    Published 2020
    “…Quantum hardware and quantum-inspired algorithms are becoming increasingly popular for combinatorial optimization. However, these algorithms may require careful hyperparameter tuning for each problem instance. …”
    Journal article
  17. 97

    Annealing-based quantum computing for combinatorial optimal power flow by Morstyn, T

    Published 2022
    “…This paper proposes the use of annealing-based quantum computing for solving combinatorial optimal power flow problems. Quantum annealers provide a physical computing platform which utilises quantum phase transitions to solve specific classes of combinatorial problems. …”
    Journal article
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