Quantum-behaved particle swarm optimization for mixed-integer nonlinear programming

doi:10.3778/j.issn.1002-8331.2010.09.015

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (9): 49-50.DOI: 10.3778/j.issn.1002-8331.2010.09.015

• 研究、探讨 • Previous Articles Next Articles

Quantum-behaved particle swarm optimization for mixed-integer nonlinear programming

ZHANG Lan^1，2，XING Zhi-dong¹

1.Mathematics Department，Northwest University，Xi’an 710127，China
2.Basic Department，Xi’an Aeronautical Polytechnic Institute，Xi’an 710089，China

Received:2009-05-05 Revised:2009-06-30 Online:2010-03-21 Published:2010-03-21
Contact: ZHANG Lan

基于量子粒子群求解混合整数非线性规划

张兰^1，2，邢志栋¹

1.西北大学数学系，西安 710127
2.西安航空职业技术学院基础部，西安 710089

通讯作者: 张兰

Abstract

Abstract: Quantum-behaved Particle Swarm Optimization（QPSO） developed on the basis of classical particle swarm optimization is a method with better convergence for mixed-integer nonlinear programming.Then the experimental results indicate that QPSO handles mixed-integer nonlinear programming problems much efficiently.It is a new way for solving mixed-integer nonlinear programming problem.

Key words: Mixed-integer NonLinear Programming（MNLP）, Quantum-behaved Particle Swarm Optimization（QPSO）, Particle Swarm Optimization（PSO）

摘要： 在经典微粒群算法的基础上提出一种有较高收敛性能的智能算法：量子粒子群（QPSO）算法。并用于求解混合整数非线性规划问题。实验室证明QPSO算法收敛性能好、速度快，为求解混合整数非线性规划开辟了新途径。

关键词: 混合整数非线性规划（MNLP）, 量子粒子群（QPSO）, 粒子群（PSO）

CLC Number:

ZHANG Lan^1，2，XING Zhi-dong¹. Quantum-behaved particle swarm optimization for mixed-integer nonlinear programming[J]. Computer Engineering and Applications, 2010, 46(9): 49-50.

张兰^1，2，邢志栋¹. 基于量子粒子群求解混合整数非线性规划[J]. 计算机工程与应用, 2010, 46(9): 49-50.

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Quantum-behaved particle swarm optimization for mixed-integer nonlinear programming

基于量子粒子群求解混合整数非线性规划

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