Trap escape for local search by backtracking and conflict reverse

Duong, Huu-Phuoc and Duong, Thach-Thao ORCID: and Pham, Duc Nghia and Sattar, Abdul and Duong, Anh Duc (2013) Trap escape for local search by backtracking and conflict reverse. In: 12th Scandinavian Conference on Artificial Intelligence (SCAI 2013), 20 Nov - 22 Nov 2013, Aalborg, Denmark.


This paper presents an efficient trap escape strategy in stochastic local search for Satisfiability. The proposed method aims to enhance local search by providing an alternative local minima escaping strategy. Our variable selection scheme provides a novel local minima escaping mechanism to explore new solution areas. Conflict variables are hypothesized as variables recently selected near local minima. Hence, a list of backtracked conflict variables is retrieved from local minima. The new strategy selects variables in the backtracked variable list based on the clause-weight scoring function and stagnation weights and variable weights as tiebreak criteria. This method is an alternative to the conventional method of selecting variables in a randomized unsatisfied clause. The proposed tiebreak method favors high stagnation weights and low variable weights during trap escape phases. The new strategies are examined on verification benchmark and SAT Competition 2011 and 2012 application and crafted instances. Our experiments show that proposed strategy has comparable performance with state-of-the-art local search solvers for SAT.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: No Faculty
Faculty/School / Institute/Centre: No Faculty
Date Deposited: 30 Mar 2022 04:49
Last Modified: 30 Mar 2022 04:49
Uncontrolled Keywords: local search; SAT; Stagnation; Trap escape
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460210 Satisfiability and optimisation
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