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    Structure in combinatorial optimization and its effect on heuristic performance

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    http://hdl.handle.net/10217/80944
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    Abstract
    The goal in combinatorial optimization is to find a good solution among a finite set of solutions. In many combinatorial problems, the set of solutions scales at an exponential or greater rate with the instance size. The maximum boolean satisfiability (MAX-SAT) is one such problem that has many important theoretical and practical applications. Due to the exponential growth of the search space, sufficiently large instances of MAX-SAT are intractable for complete solvers. Incomplete solvers, such as stochastic local search (SLS) algorithms are necessary to find solutions in these cases. Many SLS ...
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    Author(s)
    Hains, Doug

    Advisor(s)
    Whitley, Darrell; Howe, Adele

    Date Issued
    2013
    Format
    born digital; doctoral dissertations
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    • 2000-2019 - CSU Theses and Dissertations
    • Theses and Dissertations - Department of Computer Science

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