Research On Scheduling Problem Of Two Parallel Machines Considering Different Types Of Preventive Maintenance

With the continuous development of science and technology,the degree of modernization of corporates production continues to improve,the scale of corporate is becoming larger and larger,and the pressure of competition is becoming more and more fiercely.Allocating resources and energy reasonably to enhance the critical competitiveness of corporates is more and more important.During the actual production process,with the increase of producing time,the service life of related parts of production equipment will be dwinded.Once these parts are not shifted and maintained in time,it will lead to production equipment breakdown or even shutdown,causing losses to the corporate,while preventive maintenance of production equipment can effectively avoid the above situation.As a result,when corporates conduct production activities,they should combine production scheduling with equipment maintenance for strategy.In this thesis,our research focus on the research on scheduling problem of two parallel machines considering different types of preventive maintenance,and design an improved artificial fish swarm algorithm to solve the problem.The effectiveness of the model and algorithm are verified by experiments and simulation.The main research works are as follows:Firstly,the background and importance of the two parallel machine scheduling problem under preventive maintenance are elaborated.Meanwhile,the research characteristics and research status of the current problem are illustrated.The solution methods are analyzed and summarized,and the research ideas and framework of this thesis are given.Secondly,this thesis gives a clear explanation of the problems studied in this article.For the two devices in the parallel machine,different maintenance methods are used.One is flexible periodic maintenance,the maintenance duration is fixed,and the start time and end time of maintenance are decided.The other is fixed period maintenance.The maintenance duration is the proportion function of the accumulated running time of the machine after the last maintenance,and the start time and maintenance duration are decided.The mathematical programming model of the problem is established by minimizing the maximum completion time.Thirdly,considering the complexity of the problem and the non-linear characteristics of the established model,an improved artificial fish swarm algorithm is designed to solve the problem.When the artificial fish swarm algorithm is used for solving,the field of view and step length of the artificial fish have a great influence on the performance of the algorithm.This thesis considers the method of combining the artificial fish's field of view with the iteration number of the algorithm for adaptive adjustment.The step length of the artificial fish is combined with the Hamming distance between the artificial fish,and the size of the step is determined by the state difference between the artificial fish.The field of vision and step length of artificial fish are improved to improve the convergence speed of the algorithm and improve the performance of the algorithm.Finally,test cases with different problem sizes are randomly generated,and the improved artificial fish swarm algorithm is compared with artificial fish swarm algorithm and genetic algorithm to verify the accuracy of the mathematical model and the effectiveness of the algorithm.By comparing the three dimensions of the optimization goal obtained by the algorithm,the running time of the algorithm and the number of iterations of the algorithm,it is found that the improved artificial fish swarm algorithm is more suitable for the problem studied in this thesis.