Research On Distributed Permutation Flow Shop Scheduling Based On AGNES Algorithm

With the rapid development of economy,more and more enterprises pay attention to distributed shop scheduling.Therefore,how to improve the production efficiency of enterprises has become an important research field.The purpose of this paper is to explore the distributed permutation flow shop scheduling problem,in order to solve the problem of job allocation and job sequencing,and provide a reference for distributed shop.Firstly,a scheduling model was established.On this basis,the AGNES algorithm was used for hierarchical clustering of the workpieces,and combined with the NEH algorithm,the obtained clustering cluster was evenly distributed to each workshop,so as to avoid the excessively long production cycle of individual workshops.In addition,the adaptive function and the adaptive crossover mutation operator of the traditional genetic algorithm are improved,and the 2-Opt permutation operation is introduced into the genetic algorithm,so that the algorithm can get rid of the local optimal while maintaining the diversity of the population.The existing heuristic algorithm is compared with the intelligent algorithm,and its performance is evaluated.Experimental results show that both methods are relatively stable and accurate.