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A Dynamic Clause Specific Initial Weight Assignment for Solving Satisfiability Problems Using Local Search

ALGORITHMS(2021)

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摘要
For decades, the use of weights has proven its superior ability to improve dynamic local search weighting algorithms' overall performance. This paper proposes a new mechanism where the initial clause's weights are dynamically allocated based on the problem's structure. The new mechanism starts by examining each clause in terms of its size and the extent of its link, and its proximity to other clauses. Based on our examination, we categorized the clauses into four categories: (1) clauses small in size and linked with a small neighborhood, (2) clauses small in size and linked with a large neighborhood, (3) clauses large in size and linked with a small neighborhood, and (4) clauses large in size and linked with a large neighborhood. Then, the initial weights are dynamically allocated according to each clause category. To examine the efficacy of the dynamic initial weight assignment, we conducted an extensive study of our new technique on many problems. The study concluded that the dynamic allocation of initial weights contributes significantly to improving the search process's performance and quality. To further investigate the new mechanism's effect, we compared the new mechanism with the state-of-the-art algorithms belonging to the same family in terms of using weights, and it was clear that the new mechanism outperformed the state-of-the-art clause weighting algorithms. We also show that the new mechanism could be generalized with minor changes to be utilized within the general-purpose stochastic local search state-of-the-art weighting algorithms.
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关键词
artificial intelligence,dynamic local search algorithms,optimization,planning
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