Research On Permutation Flowshop Scheduling Problem Based On Swarm Intelligence Algorithm

With the rapid development of economic globalization and the arrival of big data era,customized production has gradually become the main mode of production in many fields.Enterprises tailored customized products according to customer demand,"Tastes differ all tastes." looks like to be no longer a problem.But for some products,such as pens,auto parts manufacturing,paper products,and even the vast majority of consumer goods,there is still mass production.The flow shop scheduling problem is to optimize the processing time and resources in the batch process so as to maximize the production efficiency of the enterprise.The scheduling problem is to study how to allocate the scarce resources and optimize the production efficiency.Therefore,the study of scheduling problem plays a very important role in most manufacturing,production systems and information processing applications.With the continuous expansion of production scale,how to formulate and schedule production tasks will also have more and more impact on the management and production of enterprises.A good scheduling scheme can improve the production efficiency and resource utilization of enterprises,which can make the resources be used more rationally,and also improve the market competitiveness of enterprises.In this paper,the improved swarm intelligence algorithm is used to optimize the permutation pipeline shop scheduling problem,and it is compared with other existing improvements.It can provide reference for enterprises in the optimization of flowshop scheduling.The main research contents include the following parts:(1)Studying the related literature of permutation flowshop scheduling problem.Through the relevant literature of PFSP,this paper explores the role of optimization in economic management and its engineering value,and clarifies the characteristics and significance of the study.(2)Constructing permutation flowshop scheduling problem model.This research studies the existing models of the permutation flow shop scheduling problem.The makespan and total flow time are regarded as objective function to optimal solution quality and computation time.So by this way,productivity is improved,production resources are utilized more balanced and reducing inventory.(3)Swarm intelligence algorithm is used to optimize the model.Since the permutation flow shop scheduling problem belongs to the NP-hard problem,there is no global optimization algorithm with polynomial computational complexity.The shuffled frog leaping algorithm has characteristics such as simple concept,few parameters,fast calculation,strong global searching ability and easy to realize the advantages in solving combinatorial optimization problems.The wolf packing algorithm has the advantages of global convergence and suitability for multimodal and high-dimensional functions.This paper chooses to design and improve these two algorithms to solute the model.The results of this paper expand the application of swarm intelligence algorithm and to obtain more effective optimal methods of the permutation flow shop scheduling problem,but also have certain guidance and reference significance for permutation flow shop scheduling decision.