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

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 a...

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Vydáno v:2010 International Conference on Information and Automation s. 718 - 722
Hlavní autoři: Zhengda Meng, Qinqi Chen
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2010
Témata:
Algorithm design and analysis
Analytical models
ant colony algorithm
Ant colony optimization
Arc welding robot
Design methodology
genetic algorithm
Genetic algorithms
hybrid genetic ant colony algorithm
Job design
job scheduling
Optimization methods
Robots
Scheduling algorithm
Welding
ISBN:1424457017, 9781424457014
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Shrnutí: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.
ISBN:1424457017
9781424457014
DOI:10.1109/ICINFA.2010.5512473