Improved particle swarm optimization algorithm for mixed integer nonlinear programming problems

被引：4

作者：

Li Hui-rong ^{[1
]}

Gao Yue-lin ^{[2
]}

机构：

[1] Shang Luo Univ, Dept Math & Computat Sci, Shang Luo 726000, Shanxi, Peoples R China

[2] North Natl Univ, Res Inst Informat & Syst Sci, Yin Chuan 750021, Peoples R China

来源：

MATERIALS, MECHATRONICS AND AUTOMATION, PTS 1-3 | 2011年 / 467-469卷

关键词：

mixed integer nonlinear programming; particle swarm optimization; migration operator; constraint handling techniques; EVOLUTIONARY ALGORITHMS;

D O I：

10.4028/www.scientific.net/KEM.467-469.359

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an improve particle swarm optimization algorithm for solving the mixed nonlinear integer programming problems. In this algorithm, the mixed nonlinear integer programming problems is converted into unconstrained bi-objective optimization problem by the dynamic bi-objective constraint handling methods and improved the velocity equation of PSO. Introduction of migration operator in order to overcome the premature phenomenon, retention to the better performance of infeasible particles according to the constraint violation in each iteration, it is effectively maintain the swarm diversity. Numerical experiments show that the proposed algorithm has faster convergence speed and better ability of global optimization.

引用

页码：359 / +

页数：2

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