An exploration of simulated annealing and its implementations to solve NP-hard problems

Abstract

Simulación de algoritmos aproximados para solucionar rápido problemas NP

Simulated annealing is an approximation method for NP problems that imitates annealing which is a process to change the chemical structure of a material. The idea of imitating this process is to find the global optimum of NP problems sacrificing precision for performance. This is important because NP problems take a long time to solve problems with big samples, and they could help with many real world situations. In this dissertation we will cover the queens puzzle, the traveling salesman problem and the Boolean satisfiability problem to solve them in faster times than the NP Solution with their respective implementations.