Research On Algorithm And Application For Flexible Robotic Manufacturing Cell Scheduling Problem

With the intensification of market competition and the development of advanced manufacturing technology,robotic manufacturing cell has been wildly applied in manufacturing industry.It makes scheduling problem an investigative emphasis as being the basis of robot manufacturing cell operation.In order to further reduce the cost,balance equipment load and adapt to small batch,multi-species production mode,transport operation and multi-objective optimization are required to be taken into account in research of scheduling problem.Therefore,this paper focus on the scheduling mechanism and the algorithms of two kinds of robotic manufacturing cell scheduling problem.The first subject is the flexible robotic manufacturing cell scheduling problem with multiple robots,which is described by disjunctive graph in this paper.A hybrid ant colony algorithm is proposed which improves the state transition rule and pheromone updating rule of the ant colony algorithm.Besides,the proposed algorithm combines with genetic operator and multi-robot scheduling algorithm to obtain the complete solution set.The experimental results demonstrate the effectiveness and stability of the proposed algorithm.It is also shown that the MMAS pheromone updating rule is more capable for big-scale problem than the ACS pheromone updating rule.The second problem addressed in this paper is the multi-objective flexible robotic manufacturing cell scheduling problem.An improved NSGA-II algorithm is presented with population pre-screened mechanism and improved elitist selection.The extensive computational experiments are conducted.The results show that the algorithm proposed successfully improve the population diversity while avoid prematurity,and solves the problem effectively and reliably.In the end of this paper,a prototype robot manufacturing cell scheduling system based on two algorithm proposed above is developed for actual shop manufacturing.