A study of multi-objective dynamic planning for intelligent laboratory management programs in nonlinear engineering environments

The expansion of information-based education and the growing need for computer laboratories have made their day-to-day management a key part of teaching and learning management activities. The traditional manual management method is inefficient and difficult to handle the increasingly complex management tasks. The emergence of optimized management systems has effectively improved the effectiveness and quality of computer laboratory management work, but the operational efficiency and security of management systems are also facing enormous challenges. To improve the real-time and security of management systems while efficiently completing management tasks, this paper conducted in-depth research on the design of computer laboratory optimization systems using nonlinear engineering algorithms. To verify its effectiveness, this article tested the system from three perspectives: functional implementation, running load, and security performance. The experimental results showed that at the functional implementation level, the average response time of the system for each test case requirement was 1.0767 seconds. It can be seen from the specific results that the demand response speed of the computer laboratory optimization management system based on nonlinear engineering is fast, which can efficiently handle the daily management tasks of the laboratory and promote the improvement of the quality and level of teaching management.