Chaos-Based Simulated Annealing Algorithm

Resource Overview

Implementation of chaos-based simulated annealing optimization algorithm, a computational optimization technique developed for undergraduate thesis project

Detailed Documentation

In this paper, we explore the chaos-based simulated annealing algorithm, a computational optimization method that plays a crucial role in our graduation project. The algorithm combines chaotic systems' ergodicity with simulated annealing's probabilistic acceptance criteria to escape local optima. We conduct detailed research on the algorithm's principles and applications, validating its effectiveness through experimental implementations. Key implementation aspects include chaotic map initialization (such as logistic maps), temperature scheduling, and metropolis criterion adaptation. Our objective is to solve a specific optimization problem using this chaos-enhanced approach, followed by comprehensive result analysis and evaluation. The study aims to contribute to optimization algorithm development while providing novel methodologies and insights for related research fields.