Since 3d printing is a long process, using bio-inspired algorithms to obtain the model that requires less support material and/or prints in less time

Source code for the thesis entitled "Teoría de la aproximabilidad: análisis teórico y resolución práctica mediante algoritmos genéticos."

A new optimization method based on the dynamic of sliding motion along a frictionless inclined plane. In IPO, a collection of agents cooperate with each other and move toward better positions in the search space by employing Newton’s second law and equations of motion. The standard version of the IPO is presented by Mozafari et al. in 2016. Powe…

With the aim of create a powerful trade-off between the concepts of exploitation and exploration, and rectify the complexity of their structural parameters in the standard IPO, a modified version of IPO (called MIPO) is introduced as an efficient optimization algorithm for digital infinite-impulse-response (IIR) filters model identification. The…

Multi-objective optimization based on sloping plate optimization algorithm called Multi-objective Inclined Planes system optimization algorithm (MOIPO) is presented in this link. The proposed method uses the concept of Pareto optimization to identify non-dominant positions and an external tank to maintain these positions.

This paper presents an intelligent sizing method to improve the performance and efficiency of a CMOS Ring Oscillator (RO). The proposed approach is based on the simultaneous utilization of powerful and new multi-objective optimization techniques along with a circuit simulator under a data link. The proposed optimizing tool creates a perfect trad…

Simple console implementation of the Krill Herd (KH) algorithm

Python code for ECS-NL.

A simplified and effective version of IPO (called SIPO) with the aim of simplifying the main IPO equations, creating a powerful trade-off between the concepts of exploitation and exploration, and modifying the complexity of their structural parameters.

In this project, a new ACO algorithm is proposed which ensures to solve the problems encountered in traditional ACO algorithms. This algorithm was tested on number of environments to examine efficiency, error margin and count computational time. The results ensured that the proposed ACO algorithm is completely efficient in small-scale environmen…

This repository contains my Bio-Inspired Computing Projects during University and the projects that I've implemented due to my interest in Bio-Inspired Computing. These projects include l-systems development and bio-inspired optimization methods.

AHPSO: Altruistic Heterogeneous Particle Swarm Optimisation Algorithm. Source code for the paper: IEEE SSCI https://ieeexplore.ieee.org/document/9660149

Study and implementation of bioinspired metaheuristics (ACO, CLONALG, GA, PSO)

Bio-inspired Computing

Sample Code Collection of Nature-Inspired Computational Methods

An ant colony optimization program for solving image segmentation created in the context of IT3708 at NTNU.

SPGD: Search Party Gradient Descent algorithm, a Simple Gradient-Based Parallel Algorithm for Bound-Constrained Optimization. Link: https://www.mdpi.com/2227-7390/10/5/800

Python3 framework for comparative study of recent metaheuristics

Bio inspired algorithms in Elixir

🧬This repository contains implementations of various bio-inspired optimization algorithms, along with example notebooks and resources for demonstration.