A Memory Optimized Data Structure for Binary Chromosomes in Genetic Algorithm
Neural and Evolutionary Computing
2021-03-09 v1 Artificial Intelligence
Abstract
This paper presents a memory-optimized metadata-based data structure for implementation of binary chromosome in Genetic Algorithm. In GA different types of genotypes are used depending on the problem domain. Among these, binary genotype is the most popular one for non-enumerated encoding owing to its representational and computational simplicity. This paper proposes a memory-optimized implementation approach of binary genotype. The approach improves the memory utilization as well as capacity of retaining alleles. Mathematical proof has been provided to establish the same.
Keywords
Cite
@article{arxiv.2103.04751,
title = {A Memory Optimized Data Structure for Binary Chromosomes in Genetic Algorithm},
author = {Avijit Basak},
journal= {arXiv preprint arXiv:2103.04751},
year = {2021}
}