Hybrid genetic-ant colony algorithm based job scheduling method research of arc welding robot

Author

Meng, Zhengda ; Chen, Qinqi

Author_Institution

Key Lab. of Meas. & Control of Complex Syst. of Eng., Southeast Univ., Nanjing, China

fYear

2010

fDate

20-23 June 2010

Firstpage

718

Lastpage

722

Abstract

Research of job scheduling methods of arc welding robot is focused in this paper. The job scheduling of arc welding robot is considered as a Traveling-salesman-Problem. Welding job scheduling is modeled and relevant job scheduling optimization methods are designed. Genetic algorithm and ant colony algorithm are applied to robot welding job scheduling first. Then, based on the characteristics of both algorithms, hybrid genetic ant colony algorithm is designed to improve optimization performance. With simulated weldment as the subject, genetic algorithm, ant colony algorithm and hybrid genetic ant colony algorithm are analyzed and compared by simulation. Validity of above methods is verified.

Keywords

arc welding; genetic algorithms; job shop scheduling; robotic welding; travelling salesman problems; arc welding robot; hybrid genetic ant colony algorithm; job scheduling; traveling salesman problem; Algorithm design and analysis; Analytical models; Ant colony optimization; Design methodology; Genetic algorithms; Job design; Optimization methods; Robots; Scheduling algorithm; Welding; Arc welding robot; ant colony algorithm; genetic algorithm; hybrid genetic ant colony algorithm; job scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Automation (ICIA), 2010 IEEE International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4244-5701-4

Type

conf

DOI

10.1109/ICINFA.2010.5512473

Filename

5512473