Deriving Smaller Orthogonal Arrays from Bigger Ones with Genetic Algorithm

TL;DR

This paper presents a genetic algorithm approach to derive smaller orthogonal arrays from larger ones by selectively removing lines, optimizing the resulting array to meet orthogonality constraints.

Contribution

It introduces a novel genetic algorithm with constant-weight chromosomes and specialized operators for constructing smaller orthogonal arrays from larger ones.

Findings

Successfully derived smaller orthogonal arrays using the proposed GA

The fitness function effectively guides the evolution towards arrays satisfying orthogonality

Preliminary results show the method's potential for array reduction tasks

Abstract

We consider the optimization problem of constructing a binary orthogonal array (OA) starting from a bigger one, by removing a specified amount of lines. In particular, we develop a genetic algorithm (GA) where the underlying chromosomes are constant-weight binary strings that specify the lines to be cancelled from the starting OA. Such chromosomes are then evolved through balanced crossover and mutation operators to preserve the number of ones in them. The fitness function evaluates the matrices obtained from these chromosomes by measuring their distance from satisfying the constraints of an OA smaller than the starting one. We perform a preliminary experimental validation of the proposed genetic algorithm by crafting the initial OA as a random permutation of several blocks of the basic parity-check array, thereby guaranteeing the existence of an optimal solution.