NDLI: MAX-SAT problem using evolutionary algorithms

Content Provider	IEEE Xplore Digital Library
Author	Ali, H.M. Mitchell, D. Lee, D.C.
Copyright Year	2014
Description	Author affiliation: Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC, Canada (Ali, H.M.; Mitchell, D.; Lee, D.C.)
Abstract	MAX-SAT is a classic NP-hard optimization problem. Many real problems can be easily represented in, or reduced to MAX-SAT, and thus it has many applications. Finding optimum solutions of NP-hard optimization problems using limited computational resources seems infeasible in general. In particular, all known exact algorithms for MAX-SAT require worst-case exponential time, so evolutionary algorithms can be useful for finding good quality solutions in moderate time. We present the results of an experimental comparison of the performance of a number of recently proposed evolutionary algorithms for MAX-SAT. The algorithms include the Artificial Bee Colony (ABC) algorithm, Quantum Inspired Evolutionary Algorithm (QEA), Immune Quantum Evolutionary Algorithm (IQEA), Estimation of Distribution Algorithm (EDA), and randomized Monte Carlo (MC). Our experiments demonstrate that the ABC algorithm has better performance than the others. For problems with Boolean domain, such as MAX-SAT, the ABC algorithm requires specification of a suitable similarity measure. We experimentally evaluate the performance of the ABC algorithm with five different similarity measures to indicate the better choice for MAX-SAT problems.
Starting Page	1
Ending Page	8
File Size	357723
Page Count	8
File Format	PDF
ISBN	9781479944583
DOI	10.1109/SIS.2014.7011783
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Quantum computing Sociology MAX-SAT Evolutionary computation Logic gates CNF Statistics Equations evolutionary algorithm Optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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