Research On Distributed And Flexible Job-shop Scheduling Based On Improved Shuffled Frog Leaping Algorithm

With the rapid development of economic globalization and economic integration,market competition is becoming increasingly fierce and showing an obvious international trend.China’s manufacturing industry is facing enormous challenges and opportunities at the same time.If China’s manufacturing industry wants to continue to develop better,it must break the traditional inherent production mode and actively carry out transformation and upgrading.In the process of manufacturing transformation and upgrading,more and more enterprises are gradually recognizing the importance of distributed flexible production,a multi-workshop collaborative production model.Due to the differences in technical level,material resources and equipment performance scattered throughout the workshop,the existing production scheduling mechanism is difficult to produce the ideal results.Therefore,this academic paper proposes an improved shuffled frog leaping algorithm to optimize distributed and flexible production scheduling.As a new type of pseudo-biology intelligent optimization algorithm,shuffled frog leaping algorithm has the characteristics of fewer control parameters,fast calculation speed,strong global optimization ability and easy implementation.It has been widely used to solve various combinatorial optimization problems.Based on the research on the optimization mechanism of the shuffled frog leaping algorithm,this academic paper proposes an improved shuffled frog leaping algorithm for the shortcomings of the algorithm to solve the distributed and flexible job-shop scheduling problem.The main research results obtained in this academic paper are as follows:(1)Aiming at the problem of uneven distribution of initial population in the classical shuffled frog leaping algorithm,this paper proposes the Latin hypercube sampling method to construct the initial population,which makes the frogs more evenly distributed in the feasible region,thus laying a good foundation for improving the global search ability.(2)In the local search,the adaptive mobility factor is introduced to change the moving step size,thereby improving the convergence speed and optimization precision of the algorithm.For the local search,only the worst individuals in each sub-population frog are updated.The other frogs do not perform the synchronous update operation.The frogs in the sub-population are designed to update,so that all the frogs in the subpopulation are changed better,which expands the search range and improves search accuracy.The effectiveness of the improved algorithm is verified by comparison of simulation experiments in terms of search accuracy and convergence speed.(3)Based on the in-depth analysis of the distributed and flexible job-shop scheduling problem,the corresponding mathematical model is established,and the improved shuffled frog leaping algorithm is applied to the established problem model.The coding and decoding mechanism is designed,and the key flexible manufacturing unit is used to transfer the workpiece operation and its own optimization operation in the process of searching for the optimal solution locally.The simulation results show that the improved shuffled frog leaping algorithm has good optimization performance in solving this problem.