Modified extremal optimization for the hard maximum satisfiability problem

Guo-qiang ZENG; Yong-zai LU; Wei-Jie MAO

doi:10.1631/jzus.C1000313

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Modified extremal optimization for the hard maximum satisfiability problem

Computer & Automation | Updated：2022-08-31

- Modified extremal optimization for the hard maximum satisfiability problem
- Modified extremal optimization for the hard maximum satisfiability problem
- Frontiers of Information Technology & Electronic Engineering Vol. 12, Issue 7, Pages: 589-596(2011)
- Affiliations：
  
  1.College of Physics & Electronic Information Engineering, Wenzhou University, Wenzhou 325035, China
  2.State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China
- Author bio：
  
  E-mail:zeng.guoqiang5@gmail.com
- Funds：
- DOI：10.1631/jzus.C1000313
  CLC：
- Received：09 September 2010，
  
  Revised：2011-06-03，
  
  Accepted：29 March 2011，
  
  Published：2011-07
- Accepted：
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Guo-qiang ZENG, Yong-zai LU, Wei-Jie MAO. Modified extremal optimization for the hard maximum satisfiability problem[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(7): 589-596.
DOI：

Guo-qiang ZENG, Yong-zai LU, Wei-Jie MAO. Modified extremal optimization for the hard maximum satisfiability problem[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(7): 589-596. DOI： 10.1631/jzus.C1000313.

摘要

Abstract

Based on our recent study on probability distributions for evolution in extremal optimization (EO)

we propose a modified framework called EOSAT to approximate ground states of the hard maximum satisfiability (MAXSAT) problem

a generalized version of the satisfiability (SAT) problem. The basic idea behind EOSAT is to generalize the evolutionary probability distribution in the Bose-Einstein-EO (BE-EO) algorithm

competing with other popular algorithms such as simulated annealing and WALKSAT. Experimental results on the hard MAXSAT instances from SATLIB show that the modified algorithms are superior to the original BE-EO algorithm.

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Related Institution

RISE-Centre for Research and Innovation in Software Engineering, School of Computer and Information Science, Southwest University

State Key Laboratory for High Performance Computing, School of Computer, National University of Defense Technology, Changsha 410073,China E-mail: zhimingliu88@swu.edu.cn; jiwang@ios.ac.cn Received Oct. 10, 2020; Revision accepted Oct. 16, 2020; Crosschecked Oct. 26

Department of Automation, Shanghai Jiao Tong University

Department of Automation, Zhejiang University

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