DocumentCode :
510020
Title :
Maximal Equation Satisfying Problem Solving in F2 Field by Velocity Perturbed Particle Swarm Algorithm
Author :
Xinchao, Zhao
Author_Institution :
Dept. of Math., Beijing Univ. of Posts & Telecommun., Beijing, China
Volume :
2
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
339
Lastpage :
342
Abstract :
Consider the problem MAX-SATISFY over F2, that is, given a system of m linear equations with n variables over F2, find a solution satisfying the maximal number of equations. An improved particle swarm optimization (PSO) method is proposed for computing maximal satisfying solution of a polynomial equation system with equation number being far larger than variable number in a finite field. As far as we know, it´s the first time to adopt the heuristic intelligent algorithm (PSO) to solve such discrete equations in finite field. It´s obvious that there are no solutions satisfying all the equations. So our goal is to find a solution which satisfies as many equations as possible. Four randomly generated Boolean equations are solved with sizes F2 100×20, F2 300×50, F2 500×100 and F2 1000×200. Empirical results show that algorithm has a robust performance and strong exploration and exploitation abilities.
Keywords :
particle swarm optimisation; polynomials; problem solving; Boolean equations; F2 field; discrete equations; heuristic intelligent algorithm; linear equations; maximal equation satisfying problem solving; polynomial equation system; velocity perturbed particle swarm algorithm; Ant colony optimization; Biology computing; Birds; Equations; Galois fields; Heuristic algorithms; Mathematics; Particle swarm optimization; Polynomials; Problem-solving; PSO; maximal equation satisfying problem; particle swarm optimization; velocity perturb;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.142
Filename :
5375780
Link To Document :
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