Hybridization of Improved Real-Coded Genetic, Teaching-Learning-Based Optimization and Neural Network (gaTLBO_NNA) Algorithm for Global Optimization of Functions

A. In this paper, we proposed a new hybrid algorithm for the minimization of real functions.This algorithm, called gaTLBO_NNA, is a combination of three algorithms: Improved real-coded genetic algorithm (IRGA), the Teaching-learning-based optimization (TLBO) algorithm and the Neural Network Algorithm (NNA).First we evaluated our algorithm on some benchmark test functions and compared it to some metaheuristics.The results showed that the proposed hybrid algorithm delivers better performance for most of the tested functions.We then applied our algorithm to estimate the parameters of a COVID-19 model using data from Morocco.