Flexible Job Shop Scheduling Optimization And Simulation Based On Improved Genetic Algorithm

Job shop scheduling is one of the key factors to influence the production efficiency. Theeffective scheduling strategy and optimization method can guarantee on-time delivery, reduceinventory cost, improve equipment utilization, so as to reduce the operation cost of theenterprise. The Flexible Job Shop Scheduling Problem (FJSP) breaks the uniquenessconstraint of processes’ processing resources. Each process can be completed by a plurality ofthe same or different equipment. This problem is more according to production practice. Sothe study on it has more important theoretical value and application value.Firstly, the flexible job shop scheduling problem are summarized. It is classified inaccordance with its different classification criteria such as objectives, constraints, batch andso on. The main research methods for flexible job shop scheduling problems at home andabroad has been summarized. The research development trend has been discussed through itsanalysis of the existing problems. Through the analysis of the production characteristics andproduction mode of the gear shop, double objective flexible job shop schedulingmathematical model of gear workshop has been established.Secondly, against the need to be considered the objective function of weight problemswhen solving the traditional multi-objective flexible job shop scheduling problem, animproved Non-dominated Sorting Genetic Algorithm (NSGA-II) has been designed to be usedto solve the mathematical model of flexible job shop scheduling problem. The basic idea ofthe genetic algorithm, including the operation process and operating operator of the geneticalgorithm was introduced. Elite reserve strategy and genetic operation such as reproduction,crossover and mutation have been designed detailed. It ensures that diversity of the populationevenly distributed,but also the offspring inherit the excellent characteristics of the parent. Thedesign and development of the algorithm has been carried on using Microsoft Visual C++platform. A multi-objective flexible job shop scheduling simulation system has beenestablished, and a group of Pareto set for multi-objective flexible job shop schedulingproblem can be obtained. The feasibility and effectiveness of the proposed algorithm will beverified by the instances of simulating the actual production and the testing references.Finally, against to the flexible job shop, simulation logic has been designed, and a flexible job shop scheduling simulation model has been build with the Witness as the simulationplatform. The Pareto solution of the flexible job shop scheduling simulation system will beconverted to the process route of the Witness scheduling simulation model using the excel fileas an intermediate storage of conversion data media. The integration between themulti-objective flexible job shop scheduling simulation system and the Witness schedulingsimulation model has been achieved. By running the simulation model, the operational statusof equipment of the production can be known in real time.