Maximum entropy particle swarm optimization for nonlinear l-1 norm minimization problem

doi:10.3778/j.issn.1002-8331.2009.13.018

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (13): 62-64.DOI: 10.3778/j.issn.1002-8331.2009.13.018

• 研究、探讨 • Previous Articles Next Articles

Maximum entropy particle swarm optimization for nonlinear l-1 norm minimization problem

ZHANG Jian-ke

Department of Mathematics and Physics，Xi’an Institute of Posts and Telecommunications，Xi’an 710121，China

Received:2008-03-17 Revised:2008-06-10 Online:2009-05-01 Published:2009-05-01
Contact: ZHANG Jian-ke

非线性l-1模极小化问题的极大熵粒子群算法

张建科

西安邮电学院应用数理系，西安 710121

通讯作者: 张建科

Abstract

Abstract: According to a class of nonlinear l-1 norm minimization problems，a new hybrid algorithm is proposed to combine particle swarm optimization with maximum entropy function method.Firstly，the maximum entropy function is used to transform nonlinear l-1 norm minimization problems into a smooth function of unconstrained optimization problems，this smooth function is used as particle swarm optimization’s fitness function；Then particle swarm optimization is used to optimize the problems.The numerical results show that the algorithm converges faster，numerical stability，and it is an effective algorithm for nonlinear l-1 norm minimization problems.

Key words: Particle Swarm Optimization, evolutionary computation, l-1 norm minimization Problem, maximum entropy method

摘要： 针对非线性l-1模极小化问题，利用粒子群算法并结合极大熵函数法给出了此类问题的一种新混合算法。该算法首先利用极大熵函数将非线性l-1模极小化问题转化为一个光滑函数的无约束最优化问题，将此光滑函数作为粒子群算法的适应值函数；然后应用粒子群算法来优化此问题。数值结果表明，该算法收敛快、数值稳定性好，是求解非线性l-1模极小化问题的一种有效算法。

关键词: 粒子群算法, 进化算法, l-1模极小化问题, 极大熵函数

ZHANG Jian-ke. Maximum entropy particle swarm optimization for nonlinear l-1 norm minimization problem[J]. Computer Engineering and Applications, 2009, 45(13): 62-64.

张建科. 非线性l-1模极小化问题的极大熵粒子群算法[J]. 计算机工程与应用, 2009, 45(13): 62-64.

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Maximum entropy particle swarm optimization for nonlinear l-1 norm minimization problem

非线性l-1模极小化问题的极大熵粒子群算法

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