Bio-Inspired Algorithms to Solve NP-Hard Problems
Utilized diverse optimization methods for problem‑solving, including Genetic Algorithm and SOM for TSP, Memetic Algorithm for N Queens, Ant Colony for Assignment Problem, Simulated Annealing for Cutting Stock, and PSO for global optimum discovery.
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Overview This project implements a Self-Organizing Map (SOM) to solve the Traveling Salesman Problem (TSP). SOM is an unsupervised machine learning...
Overview The Particle Swarm Optimization (PSO) Algorithm is a computational method used to optimize a problem iteratively by improving candidate solutions....
Introduction The Cutting Stock Problem is a challenging optimization problem that arises in various industries, including paper manufacturing and sheet metal...
Introduction The N Queens problem is a classic problem in combinatorial optimization. It involves placing N chess queens on an N×N...
This project focuses on solving the assignment problem using Colony Optimization with Python. The assignment problem involves assigning n agents to...
Introduction This project implements a Genetic Algorithm in Python to solve the Traveling Salesman Problem (TSP). The TSP is a well-known...