Research On Parallel Machine Scheduling Problem Considering Production Adjustment Time Under The Constraint Of Shared Flexible Resources

With the arrival of Industry 4.0 era,under the background of continuous innovation of science and technology and continuous improvement of informatization level in various fields,the manufacturing industry began to develop towards intelligent manufacturing,lean production and other directions.In addition,with the rise of customized production mode of customer to business(C2B),it also gave birth to the production mode of multi variety and small batch,leading to frequent switching of various production tasks on equipment,which is easy to cause capacity waste and equipment loss.At the same time,in the process of parallel machine production,it is often necessary to share some auxiliary resources,such as manpower,specific production equipment,inventory buffer,etc.These resources are generally shared by multiple production lines or equipment,so sophisticated production scheduling plans are needed to reasonably coordinate the use of multiple shared resources and reduce capacity waste.In addition,in the actual production process,processing equipment needs a certain adjustment time to prevent production overload and production interruption.However,in the existing parallel machine scheduling problems,there is little research on sharing flexible resources and production adjustment time.Focusing on the above problems,this paper takes the parallel machine scheduling problem as the research object,and studies the parallel machine scheduling problem considering production adjustment time under the constraint of shared flexible resources,which has certain practical significance for the development of manufacturing industry and the digital transformation of enterprises.In this paper,the actual workshop production process is deeply analyzed in the existing unrelated parallel machine scheduling problem.Firstly,an uncorrelated parallel machine scheduling model under shared flexible resource constraints is established,and the human resource equilibrium constraints and capacity constraints in each production stage are studied.The model is solved based on NSGA-II algorithm.This paper further analyzes the impact of multiple shared flexible resources through numerical simulation of different sizes.The experimental results show that the increase of human resources and shared production line capacity will improve the scheduling goal,but the marginal effect of these two shared resources will decrease accordingly.In addition,the use of resources and capacity expansion require a certain cost,so it is very important to scientifically select the appropriate level of human resources and share the capacity of the production line to improve the productivity of the entire production system.On this basis,this paper further constructs a parallel machine scheduling model with production adjustment time constraints,and proposes a tabu search based hyper heuristic algorithm to solve the model.The algorithm selects tabu search as a High-level heuristic strategy(HLH),and combines the scheduling characteristics of unrelated parallel machine problems to design seven Low-level Heuristics methods(LLH)to form a low-level Heuristic method pool.In order to verify the effectiveness of the algorithm,numerical experiments of different sizes are constructed for simulation analysis,and compared with NSGA-II and solver based accurate algorithms.The experimental results show that the super heuristic algorithm based on tabu search is stable and efficient in solving the parallel machine scheduling problem with production adjustment time under the constraint of shared flexible resources.