Research On Open Shop Scheduling Problem With AGV Based On Hybrid Evolutionary Algorithm

With the renewal of diversified manufacturing equipment and technology required by the society and the deepening of the concept of green manufacturing,the production scheduling of the current manufacturing industry is facing a huge challenge.AGV as a flexible and efficient conveying equipment in the manufacturing system has been widely used.The main research contents for AGV open shop scheduling are as follows:For the open shop scheduling problem,the mathematical model and the disjunctive graph model are established.Combined with the disjunctive graph model,the critical path and key block are extracted,and the hybrid neighborhood search and genetic algorithm are designed.The results of standard test set show that the hybrid algorithm is effective for different scale open shop scheduling problems.To solve the single objective open shop scheduling problem with AGV,a new disjunctive graph model with AGV was constructed by analyzing the characteristics of the problem.Four connection arcs of AGV-AGV,AGV-AGV-AGV,process-process and process-AGV-process in the extraction diagram are emphatically analyzed.Various neighborhood structures based on connection arc are designed and a hybrid variable neighborhood search genetic algorithm is proposed.The experimental results show that the hybrid algorithm can obtain better solutions,and the neighborhood structure based on the connection arc can effectively improve the local search ability of the algorithm.To solve the energy efficiency scheduling problem of multi-objective open shop with AGV,a mathematical model considering production efficiency and energy consumption was established.Meanwhile,a MOEA/D algorithm based on variable neighborhood search is proposed.Combining with the above disjunctive graph model,the algorithm designs a variety of neighborhood structures based on connection arcs.The Pareto solution set of multi-objective open shop scheduling problem with AGV is obtained by applying it to a single individual.The experimental case shows that the hybrid variable neighborhood search method can get a better solution set.Finally,the results and innovations of this paper are summarized,and the future research direction is prospected.