An Order-Based GA for Robot-Based Assembly Line Balancing Problem
In the real world, there are a lot of scenes from which the product is made by using the robot, which needs different assembly times to perform a given task, because of its capabilities and specialization. For a robotic assembly line balancing (rALB) problem, a set of tasks have to be assigned to stations, and each station needs to select one robot to process the assigned tasks. In this paper, we propose a hybrid genetic algorithm (hGA) based on an order encoding method for solving rALB problem. In the hGA, we use new representation method. Advanced genetic operators adapted to the specific chromosome structure and the characteristics of the rALB problem are used. In order to strengthen the search ability, a local search procedure is integrated under the framework the genetic algorithm. Some practical test instances demonstrate the effectiveness and efficiency of the proposed algorithm.
KeywordsBalancing Improvement Genetic algorithms Local search Neighborhood structure Robotic assembly line
This work is partly supported by the National Natural Science Foundation of China under Grant 61572100, and in part by the Grant-in-Aid for Scientific Research (C) of Japan Society of Promotion of Science (JSPS) No. 15K00357.
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