# Chaotic Genetic Algorithm and The Effects of Entropy in Performance Optimization

arXiv: https://arxiv.org/abs/1903.01896 · HTML: https://mlsanity.com/paper/1903.01896/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jan 2019.

## Built on by (most cited first, 1 of 1)

- [Multi-Objective Optimization for Value-Sensitive and Sustainable Basket Recommendations](https://mlsanity.com/paper/2111.05944/) (2021)

## Abstract (arXiv)

This work proposes a new edge about the Chaotic Genetic Algorithm (CGA) and the importance of the entropy in the initial population. Inspired by chaos theory the CGA uses chaotic maps to modify the stochastic parameters of Genetic Algorithm (GA). The algorithm modifies the parameters of the initial population using chaotic series and then analyzes the entropy of such population. This strategy exhibits the relationship between entropy and performance optimization in complex search spaces. Our study includes the optimization of nine benchmark functions using eight different chaotic maps for each of the benchmark functions. The numerical experiment demonstrates a direct relation between entropy and performance of the algorithm.