The teaching-learning-based optimization (TLBO) algorithm is finding a large number of
applications in different fields of engineering and science since its introduction in 2011. The …

Proton exchange membrane fuel cells (PEMFCs) are promising devices for converting
chemical energy into electrical energy due to their versatile properties, such as high power …

This chapter introduces teaching-learning-based optimization (TLBO) algorithm and its elitist
and non-dominated sorting multiobjective versions. Two examples of unconstrained and …

This paper presents a new optimization method called GOTLBO (generalized oppositional
teaching learning based optimization) to identify parameters of solar cell models. GOTLBO …

An outlier is a datum that is far from other data points in which it occurs. It can have a
considerable impact on the output. Therefore, removing or resolving it before the analysis is …

This paper presents a novel quasi-oppositional teaching learning based optimization
(QOTLBO) methodology in order to find the optimal location of distributed generator to …

Although they are among the most researched real world engineering design problems, it is
encountered with significant problems in the optimization of structural truss bar problems …

Over past few decades, swarm intelligent algorithms based on the intelligent behaviors of
social creatures have been extensively studied and applied for all kinds of optimization …

The primary objective of this study is to delve into the application and validation of the
Resistance Capacitance Optimization Algorithm (RCOA)—a new, physics-inspired …

This work proposes the implementation of a recently invented meta-heuristic optimization
solver namely, an adaptive multiple teams perturbation-guiding Jaya (AMTPG-Jaya) …