• CN：11-2187/TH
• ISSN：0577-6686

• 数字化设计与制造 •

### 基于多层编码的遗传-粒子群融合算法流水线优化控制

1. 西安科技大学电气与控制工程学院
• 出版日期:2015-05-05 发布日期:2015-05-05

### Optimization of Flow-shop Control by Using Genetic-particle Swarm Algorithm of Multilayer-coded

HOU Yuanbin, XUE Fei, ZHENG Maoquan, FAN Rong

1. College of Electrical and Control Engineering, Xi’an University of Science and Technology
• Online:2015-05-05 Published:2015-05-05

Abstract: A genetic-particle swarm optimization algorithm of multilayer-coded is proposed to solve the flow shop’s optimizing control problem of machinery industry. The objective of the issue is to minimize the production time. Through analyzing the actual machining conditions, control mathematical model of production line is set up. The algorithm bases on particle swarm algorithm and combines the genetic swarm optimization with the multilayer-coded mechanism. The algorithm has a higher speed and is used to avoid being trapped into local minima. The results show that the multilayer-coded genetic-particle swarm optimization algorithm has saved 9% times from the basic genetic algorithm. It has advantages of improving utilization ratio and production efficiency in machining line.