The optimum selection of parameters is great important for the final quality of product in
modern industrial manufacturing process. In order to achieve highly product quality, an …

Economic load dispatch (ELD) is of great significance for energy saving and emission
reduction in power systems. However, many practical constraints and nonlinear …

This paper proposes a meta-heuristic algorithm named as quasi-oppositional self-learning
teacher-learner-based-optimization (QOSLTLBO) for solving non-convex economic load …

The location selection of logistics distribution centers is a crucial issue in the modern urban
logistics system. In order to achieve a more reasonable solution, an effective optimization …

This paper is devoted to designing higher-order adaptive PID controllers as a new
generation of PID controllers for chaos synchronization, in which second order integration …

Aiming at the problem that conventional tracking algorithms are difficult to deal with abrupt
motion efficiently, an optimization algorithm called hybrid Teaching-learning-based …

Recently, teaching‐learning‐based optimization (TLBO), as one of the emerging nature‐
inspired heuristic algorithms, has attracted increasing attention. In order to enhance its …

Finding an optimal set of discriminative features is still a crucial but challenging task in
biomedical science. The complexity of the task is intensified when any of the two scenarios …

A new hybrid algorithm named teaching–learning-based Cuckoo Search (TLCS) is
proposed for constrained optimization problems. The TLCS modifies the Cuckoo Search …

In this work, a Single Phase Multi-Group Teaching Learning Optimization strategy is
proposed which is a variant of the Teaching Learning Based Optimization algorithm. The …