A Taxonomy of Exact Methods for Partial Max-SAT  

作　　者：Mohamed El Bachir Menai Tasniem Nasser Al-Yahya 

机构地区：[1]Department of Computer Science, College of Computer and Information Sciences, King Saud University

出　　处：《Journal of Computer Science & Technology》2013年第2期232-246,共15页计算机科学技术学报（英文版）

基　　金：supported by the Research Center of College of Computer and Information Sciences at King Saud University, Saudi Arabia

摘　　要：Partial Maximum Boolean Satisfiability （Partial Max-SAT or PMSAT） is an optimization variant of Boolean satisfiability （SAT） problem, in which a variable assignment is required to satisfy all hard clauses and a maximum number of soft clauses in a Boolean formula. PMSAT is considered as an interesting encoding domain to many reaHife problems for which a solution is acceptable even if some constraints are violated. Amongst the problems that can be formulated as such are planning and scheduling. New insights into the study of PMSAT problem have been gained since the introduction of the Max-SAT evaluations in 2006. Indeed, several PMSAT exact solvers have been developed based mainly on the Davis- Putnam-Logemann-Loveland （DPLL） procedure and Branch and Bound （B^B） algorithms. In this paper, we investigate and analyze a number of exact methods for PMSAT. We propose a taxonomy of the main exact methods within a general framework that integrates their various techniques into a unified perspective. We show its effectiveness by using it to classify PMSAT exact solvers which participated in the 2007~2011 Max-SAT evaluations, emphasizing on the most promising research directions.Partial Maximum Boolean Satisfiability （Partial Max-SAT or PMSAT） is an optimization variant of Boolean satisfiability （SAT） problem, in which a variable assignment is required to satisfy all hard clauses and a maximum number of soft clauses in a Boolean formula. PMSAT is considered as an interesting encoding domain to many reaHife problems for which a solution is acceptable even if some constraints are violated. Amongst the problems that can be formulated as such are planning and scheduling. New insights into the study of PMSAT problem have been gained since the introduction of the Max-SAT evaluations in 2006. Indeed, several PMSAT exact solvers have been developed based mainly on the Davis- Putnam-Logemann-Loveland （DPLL） procedure and Branch and Bound （B^B） algorithms. In this paper, we investigate and analyze a number of exact methods for PMSAT. We propose a taxonomy of the main exact methods within a general framework that integrates their various techniques into a unified perspective. We show its effectiveness by using it to classify PMSAT exact solvers which participated in the 2007~2011 Max-SAT evaluations, emphasizing on the most promising research directions.

关 键 词：Partial Max-SAT Davis-Putnam-Logenmann-Loveland branch and bound unsatisfiability pseudo-Boolean optimization 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]