Research On Simulation And Optimization Problems Of Uncertain Job Shop Scheduling Based On Plant Simulation

Uncertain job shop scheduling problem(JSP)is a key problem that needs to be solved urgently in the field of manufacturing systems.The real-time operation of workshop scheduling is often accompanied by uncertain disturbance factors such as uncertain processing time and random machine failures.These disturbance factors will affect the normal operation of the entire workshop scheduling system.Therefore,it is necessary to consider how to deal with the uncertain disturbance factors in the workshop scheduling process,and how to respond to the uncertain disturbance factors in time and make dynamic adjustments has become a problem that must be considered in the entire manufacturing system field.In this paper,based on the simulation technology method,the uncertain JSP is researched.The modeling and solving method of the JSP with uncertain processing time and the efficient solution method of JSP under double disturbance factors are respectively studied in depth.Aiming at the JSP with uncertain processing time,analyzing the uncertain processing time of jobs’ operations,interval number is used to describe the uncertain processing time,and the method of interval number based on Plant Simulation is designed.Based on Plant Simulation simulation platform,the simulation model of JSP with uncertain processing time is established,and an optimization method based on Plant Simulation combined with genetic algorithm(GA)was used to solve the model.Benchmark examples are used to test the effectiveness of the model and solution method.The experimental results verify that the model and the solution method are effective.Among the 48 sets of examples,the calculation results of 28 sets of examples are more prominent.Based on the above research theoretical results,for solution method of the JSP with uncertain processing time,two optimization strategies for the shortest processing time(SPT)scheduling rule and heuristic Johonson algorithm to optimize the initial population of GA are proposed,two optimization methods of GA+SPT and GA+Johonson are designed to improve GA,and used the optimization method based on Plant Simulation combined with improved GA to solve the JSP with uncertain processing time.Test cases are used to test the performance of three optimization methods including the basic GA,GA+SPT and GA+Johonson.The calculation results of the examples show that the optimization method based on GA+Johonson has better solution performance,among the calculation results of the 48 sets of examples,30 sets of examples have a higher improvement rate,which can highlight the superiority of the GA+Johonson optimization method.For JSP under double disturbance factors,the simulation model of JSP under double disturbance factors is established based on the Plant Simulation simulation platform.In this model,interval numbers are used to describe uncertain processing time,and random probability distribution functions(exponential distribution functions)are introduced to characterize random machine failures.The optimization method based on Plant Simulation combined with improved GA is used to solve the JSP under double disturbance factors.Designed 24 sets of examples under two different disturbance factors including certain processing time+machine failures and uncertain processing time+machine failures,and used these examples respectively to test the performance of three optimization methods containing the basic GA,GA+SPT and GA+Johonson under different failures repair time(tr)level(set tr=5min,10 min,20min),and the calculation results of the examples verify that the optimization method of GA+Johonson has better solution performance and higher solution efficiency.Among the 24 sets of examples,18 sets of examples have better results.Combining the above theoretical results,according to the actual production situation of the actual production workshop where a packaging machine,a flat disposable mask machine and an automatic double-sided labeling machine are located respectively,the uncertain disturbance factors that actually exist in these workshops are analyzed.Applying the above-mentioned research theoretical results to these three examples,the example results verify that the model and optimization method proposed in this paper are very effective.Finally,the research results are summarized,and the future research work is prospected.