Research On Flexible Job-shop Scheduling Problem Of Intelligent Factory Based On Improved Seagull Optimization Algorithm

The manufacturing industry plays an important role in consolidating the economic foundation.The state attaches more and more importance to the manufacturing industry.The traditional workshop production has been unable to meet the production requirements,so the construction of intelligent factory is the trend of the future development of the manufacturing industry.In the process of building an intelligent factory,it is necessary and feasible to give reasonable and scientific methods while clarifying the requirements.Based on the demand of intelligent factory,this paper establishes the production architecture of intelligent factory,and explains the scheduling method in detail.First of all,the paper analyzes the traditional enterprise the problems that arise in the process of the construction of intelligent factory demand for intelligent plant are analyzed,and gives the solution based on the requirement of intelligent factory,finally based on the demand of intelligent architecture,factory production has been clear about the architecture of the connection between the content of each module and each module.Secondly,a Improved Seagull Optimization Algorithm(ISOA)is designed to initialize the population using the initialization method based on Logstic chaotic map,and a new local search model is designed.It improves the shortcoming that the seagull optimization algorithm has slow convergence and is easy to fall into local optimum at the early stage of iteration.The performance of ISOA is verified by comparing with Genetic Algorithm(GA),Seagull Optimization Algorithm(SOA)and Grey Wolf Optimizer(GWO).Furthermore,the Flexible Job-shop Scheduling Problem(FJSP)is solved by using ISOA.In the first stage,considering the cost of energy consumption and the penalty cost of tardiness,a multi-plant workpiece allocation model with the goal of minimizing the cost is established.Through simulation comparison,the proposed model can be better solved by ISOA compared with the competitive algorithm.In the second stage,the model of FJSP with the target of maximum completion time is established,and the scheduling coding is carried out by using the two-layer coding method,and the solution is solved by using ISOA in medium scale,large scale and super large scale FJSPs.The experimental results show that ISOA is better than the comparison algorithm in different degrees.Finally,a multi-objective scheduling method based on priority calculation and ISOA was designed,and the fuzzy scheduling objectives of production processes and machines were considered,and the corresponding evaluation criteria were established.Priorities were calculated using the Analytic Hierarchy Process(AHP)and the fuzzy membership function.Then,a comprehensive income model was established,which transformed the fuzzy multi-objective problem into a single objective problem to maximize the comprehensive income,thus simplifying the difficulty of factory production scheduling in complex environment.