Teaching-Learning-Based Optimization (TLBO) Algorithm

The Teaching-Learning-Based Optimization (TLBO) algorithm is a powerful artificial intelligence technique comparable to genetic algorithms. It can be applied to various domains including optimization problems and scheduling/sequencing tasks. The fundamental principle of TLBO involves simulating group learning behaviors in educational processes to optimize problem solutions. Key implementation aspects include two main phases: the Teacher Phase, where the best solution (teacher) improves the mean performance of the class, and the Learner Phase, where students interact and learn from each other through random pairing and knowledge exchange. The algorithm features high efficiency, strong robustness, and straightforward implementation, making it widely adopted in engineering and scientific research. TLBO demonstrates significant utility in industrial production optimization scheduling as well as solving complex optimization challenges in artificial intelligence applications, requiring no algorithm-specific parameters unlike many other optimization techniques.