DocumentCode :
3052133
Title :
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
Link To Document :
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