Research And Application Of Automatic Scheduling Technology Based On Hybrid Intelligent Optimization Algorithm

With the promotion and implementation of the “Industry 4.0” and “Made in China2025”,the demand for intelligent transformation in traditional manufacturing industries is becoming increasingly urgent.However,many discrete manufacturing companies still face challenges in production scheduling,such as excessive dependence on labor,inaccuracy of scheduling,waste of resources,etc.These issues not only affect competitiveness and production efficiency,but also delay the process of intelligent transformation.To address these issues,automatic scheduling technology has been proposed,which uses information technology,optimization algorithms and artificial intelligence to improve the accuracy and adaptability of scheduling.To apply automatic scheduling technology in the discrete manufacturing workshop,this paper first models the practical problem,then studies and improves intelligent optimization algorithm,and finally designs and implements automatic scheduling system.The specific contents are as follows:(1)By analyzing the actual production requirements of discrete manufacturing shops,a many-objective flexible job shop scheduling problem(MaOFJSP)model with setup time and group constraints is proposed.The most important performance of the workshop is summarized,and the optimization objectives are determined to be minimizing the maximum completion time,maximum machine load,total machine load,total tardiness,and total setup time.(2)To solve the MaOFJSP with setup time and group constraints,a hybrid intelligent optimization algorithm is proposed.The algorithm is based on the nondominated sorting genetic algorithm Ⅲ(NSGA-Ⅲ).To optimize the performance of NSGA-Ⅲ,the population initialization method was improved to enhance the quality of the initial population,the elite preservation strategy was improved to maintain the diversity of the population,and the variable neighborhood search algorithm was introduced to improve the search capability.Finally,the effectiveness and superiority of the optimization strategies are verified through comparative experiments.(3)Based on the business characteristics of discrete manufacturing,an automatic scheduling system is designed and implemented.The MaOFJSP model and the hybrid intelligent optimization algorithm proposed above are integrated.The system could provide a set of optimal scheduling solutions according to customer demand,to verify the application value of automatic scheduling technology.