Improving the Search by Encoding Multiple Solutions in a Chromosome

TL;DR

This paper explores encoding multiple solutions within a single chromosome in genetic programming, demonstrating that this approach enhances the search process without increasing decoding complexity.

Contribution

It introduces a method to encode multiple solutions in one chromosome and analyzes three genetic programming techniques for this purpose.

Findings

Encoding multiple solutions improves search efficiency.

Decoding complexity remains comparable to single-solution encoding.

Numerical experiments validate the effectiveness of the approach.

Abstract

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.