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Solving the weighted MAX-SAT problem using the dynamic convexized method

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Abstract

Satisfiability (SAT) and maximum satisfiability (MAX-SAT) are difficult combinatorial problems that have many important real-world applications. In this paper we investigate the performance of the dynamic convexized method based heuristics on the weighted MAX-SAT problem. We first present an auxiliary function which is constructed based on a penalty function, and minimize the function by a local search method which can escape successfully from previously converged local minimizers by increasing the value of a parameter. Two algorithms of the approach are implemented and compared with the Greedy Randomized Adaptive Search Procedure (GRASP) and the GRASP with Path Relinking (GRASP + PR). Experimental results illustrate efficient and faster convergence of our two algorithms.

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Authors and Affiliations

  1. Center for Discrete Mathematics and Theoretical Computer Science, Fuzhou University, Fuzhou , 350108, China

    Wenxing Zhu & Yuanhui Yan

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  1. Wenxing Zhu
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  2. Yuanhui Yan
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Correspondence to Wenxing Zhu.

Additional information

This work was supported in part by the National Science Foundation of China (NSFC) under Grants 61170308 and 10931003, in part by the National Key Basic Research Special Foundation (NKBRSF) of China under Grant 2011CB808000.

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Zhu, W., Yan, Y. Solving the weighted MAX-SAT problem using the dynamic convexized method. Optim Lett 8, 359–374 (2014). https://doi.org/10.1007/s11590-012-0583-4

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