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.
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