As a big decision in enhancing the community benefits associated with operating schools in the creation of higher education in China, teacher mutual employment administration is a crucial tool for sharing excellent teacher resources, complementing each other’s advantages, and achieving mutual benefit and win-win among colleges and universities. However, there is a problem with inaccurate evaluation of the management system. When it comes to educational growth, the conventional model of teaching is inadequate and unfair since it fails to address the issue of mutual employment management. For that reason, this research suggests an ant colony algorithm to study creative teacher mutual employment management. To begin, skills are evaluated using educational theory, and indicators are split according to mutual employment management needs in order to prevent the interference of mutual employment management. Following this, the educational theory conducts an analysis of the teacher mutual employment management system, formulates a strategy for mutual employment management, and last, synthesizes the outcomes. Under certain assessment conditions, a MATLAB simulation demonstrates that the ant colony method provides accurate results for managing instructors’ mutual employment and school operations. Compared to the old-fashioned way of teaching, they’re all better.

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Research on Ant Colony Algorithm and Its Application in Teacher Mutual Employment Management

  • Jun Lang

摘要

As a big decision in enhancing the community benefits associated with operating schools in the creation of higher education in China, teacher mutual employment administration is a crucial tool for sharing excellent teacher resources, complementing each other’s advantages, and achieving mutual benefit and win-win among colleges and universities. However, there is a problem with inaccurate evaluation of the management system. When it comes to educational growth, the conventional model of teaching is inadequate and unfair since it fails to address the issue of mutual employment management. For that reason, this research suggests an ant colony algorithm to study creative teacher mutual employment management. To begin, skills are evaluated using educational theory, and indicators are split according to mutual employment management needs in order to prevent the interference of mutual employment management. Following this, the educational theory conducts an analysis of the teacher mutual employment management system, formulates a strategy for mutual employment management, and last, synthesizes the outcomes. Under certain assessment conditions, a MATLAB simulation demonstrates that the ant colony method provides accurate results for managing instructors’ mutual employment and school operations. Compared to the old-fashioned way of teaching, they’re all better.