Deriving Smaller Orthogonal Arrays from Bigger Ones with Genetic Algorithm

• URL: http://arxiv.org/abs/2111.13047v1
• Date: Thu, 25 Nov 2021 12:06:24 GMT
• Title: Deriving Smaller Orthogonal Arrays from Bigger Ones with Genetic Algorithm
• Authors: Luca Mariot
• Abstract summary: We consider the problem of constructing a binary array starting from a bigger one, by removing a specified amount of lines. We develop a genetic algorithm where the underlying chromosomes are constant-weight binary strings that specify the lines to be cancelled from the starting OA. 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.
• Score: 1.370633147306388
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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