Research On Optimization Of Ship Design Task Scheduling Based On Improved Immune And BP Algorithm

From the beginning of the bulk carrier to now the large cruise ship,with the continuous development of the country,our ship industry is rising rapidly.In the international shipbuilding market,China’s shipbuilding industry has been the largest in terms of share for 13 consecutive years,and is moving towards becoming one of the most competitive shipbuilding centers in the world.The importance of design is prominent throughout the entire life cycle of ship products.The domestic industry focuses on optimization research in the field of ship production,performance,and other aspects,but lacks focused research on the ship design stage itself,with a large optimization interval.In summary,this article conducts research on ship design task scheduling methods to improve the efficiency and quality of ship design task execution,and proposes the establishment of scheduling optimization strategies.Based on research,the characteristics of ship design tasks are analyzed,and combined with the actual scheduling methods of existing ship design tasks,static scheduling models for ship design tasks and dynamic scheduling models for ship design tasks are established.Suitable methods are designed for optimization and solution.The main research work is as follows.Aiming at solving how to improve the efficiency of ship design and shorten the completion time of design task in the static scheduling environment.Based on the detailed analysis of ship design task design process and realistic constraints,this paper proposes to solve the problem from the optimization of design task scheduling scheme.Based on the designed task scheduling objectives,a Duration Efficiency Relevance Priority Traversal Task Scheduling Strategy(DERPT)was designed,and the solving rules and processes of the immune algorithm were optimized to improve the speed and accuracy of the solution.Finally,a case study was used to verify the feasibility and effectiveness of this method.Aiming at the dynamic scheduling optimization problem of ship design tasks,this paper analyzes the attributes of each subject involved in the problem,and proposes adding a task schedulability prediction link in the dynamic scheduling process to maximize the cumulative value of all tasks executed within the same time period,aiming to make the entire design process more stable for scheduling optimization.Combining with real-world constraint models,a BP neural network incorporating momentum adaptive thinking is used to predict the schedulability of design tasks,and then the new task set optimized through prediction is dynamically scheduled.Finally,the case proves that the scheduling scheme with predictive processing can achieve the objective of dynamic scheduling optimization well.Finally,based on the research on the above issues,the ship design task scheduling management system is designed and developed using tools such as Python language,B/S architecture,and My SQL database to assist in achieving scientific scheduling of ship design tasks and further validate the feasibility of the research results in this paper.