This repository serves as a central hub, integrating three distinct projects, each demonstrating unique applications of optimization algorithms. Below are detailed overviews and links to the individual repositories:

This project focuses on forecasting the number of queries to the NASA website. Utilizing a Multi-Layer Perceptron (MLP), the neural network weights are further optimized using various metaheuristics optimization algorithms including Grey Wolf Optimization (GWO), Particle Swarm Intelligence (PSO), and Imperialist Competitive Algorithm (ICA). This approach significantly reduces the mean absolute percentage error (MAPE) on the test set, showcasing the efficacy of these optimization techniques​.

In this project, a robot navigates to a target while avoiding obstacles and minimizing the travel distance. The environment includes randomly shaped barriers, with fixed starting and ending points. The path to the target is determined using a Genetic Algorithm (GA), exemplifying an innovative approach to robot path planning​.

This project involves deploying low-power nodes in WSNs to collect field data efficiently. It introduces a novel routing strategy using Ant Colony Optimization, a swarm intelligence-based method. This strategy is particularly tailored for WSNs with stable nodes, optimizing the data-gathering process in terms of energy efficiency