# Improving the Search by Encoding Multiple Solutions in a Chromosome

arXiv: https://arxiv.org/abs/2110.11239 · HTML: https://mlsanity.com/paper/2110.11239/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 27 references that are in the map.
- First posted on arXiv 13 Oct 2021.

## Builds on (most cited first, 1 of 1)

- [Evolving Evolutionary Algorithms using Multi Expression Programming](https://mlsanity.com/paper/2109.13737/) (2021)

## Abstract (arXiv)

We investigate the possibility of encoding multiple solutions of a problem in a single chromosome. The best solution encoded in an individual will represent (will provide the fitness of) that individual. In order to obtain some benefits the chromosome decoding process must have the same complexity as in the case of a single solution in a chromosome. Three Genetic Programming techniques are analyzed for this purpose: Multi Expression Programming, Linear Genetic Programming, and Infix Form Genetic Programming. Numerical experiments show that encoding multiple solutions in a chromosome greatly improves the search process.