A Quantum Inspired Particle Swarm Algorithm for Solving the Maximum Satisfiability Problem

被引：0
|
作者：
Layeb, Abdesslem [1 ]
机构：
[1] Mentouri Univ Constantine, MISC Lab, Dept Comp Sci, Constantine, Algeria
来源：
INTERNATIONAL JOURNAL OF COMBINATORIAL OPTIMIZATION PROBLEMS AND INFORMATICS | 2010年 / 1卷 / 01期
关键词：
Maximum Satisfiabilty problem; Quantum Particle Swarm Optimization; Local search;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper we investigate the use of quantum particle swarm optimization (QPSO) principles to resolve the satisfiability problem. We describe QPSOSAT, a new iterative approach for solving the well known Maximum Satisfiability problem (MAX-SAT). This latter has been shown to be NP-hard if the number of variables per clause is greater than 3. The basic idea is to harness the optimization capabilities of QPSO algorithm to achieve good quality solutions for Max Sat problem. To enhance the efficiency of the QPSO algorithm, a local search has been used. The obtained results are very promising and show the feasibility and effectiveness of the proposed hybrid approach.
引用
收藏
页码：13 / 23
页数：11
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