The design of binary error-correcting codes is a challenging optimization problem with several applications in telecommunications and storage, which has been addressed with metaheuristic techniques such as evolutionary algorithms. Still, all these efforts are focused on optimizing the minimum distance of unrestricted binary codes, i.e., with no constraints on their linearity, which is a desirable property for efficient implementations. In this paper, we present an Evolutionary Strategy (ES) algorithm that explores only the subset of linear codes of a fixed length and dimension. We represent the candidate solutions as binary matrices and devise variation operators that preserve their ranks. Our experiments show that up to length n= 14, our ES always converges to an optimal solution with a full success rate, and the evolved codes are all inequivalent to the Best-Known Linear Code (BKLC) given by MAGMA. On the other hand, for larger lengths, both the success rate of the ES as well as the diversity of the codes start to drop, with the extreme case of (16, 8, 5) codes which all turn out to be equivalent to MAGMA’s BKLC.

Carlet, C., Mariot, L., Manzoni, L., Picek, S. (2023). Evolutionary Strategies for the Design of Binary Linear Codes. In Evolutionary Computation in Combinatorial Optimization 23rd European Conference, EvoCOP 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (pp.114-129). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-30035-6_8].

Evolutionary Strategies for the Design of Binary Linear Codes

Mariot, Luca
;
Manzoni, Luca;
2023

Abstract

The design of binary error-correcting codes is a challenging optimization problem with several applications in telecommunications and storage, which has been addressed with metaheuristic techniques such as evolutionary algorithms. Still, all these efforts are focused on optimizing the minimum distance of unrestricted binary codes, i.e., with no constraints on their linearity, which is a desirable property for efficient implementations. In this paper, we present an Evolutionary Strategy (ES) algorithm that explores only the subset of linear codes of a fixed length and dimension. We represent the candidate solutions as binary matrices and devise variation operators that preserve their ranks. Our experiments show that up to length n= 14, our ES always converges to an optimal solution with a full success rate, and the evolved codes are all inequivalent to the Best-Known Linear Code (BKLC) given by MAGMA. On the other hand, for larger lengths, both the success rate of the ES as well as the diversity of the codes start to drop, with the extreme case of (16, 8, 5) codes which all turn out to be equivalent to MAGMA’s BKLC.
paper
Algebraic normal form; Boolean functions; Error-correcting codes; Evolutionary strategies; Variation operators;
English
23rd European Conference on Evolutionary Computation in Combinatorial Optimisation, EvoCOP 2023, held as part of EvoStar 2023 - 12 April 2023through 14 April 2023
2023
Evolutionary Computation in Combinatorial Optimization 23rd European Conference, EvoCOP 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings
9783031300349
2023
13987 LNCS
114
129
reserved
Carlet, C., Mariot, L., Manzoni, L., Picek, S. (2023). Evolutionary Strategies for the Design of Binary Linear Codes. In Evolutionary Computation in Combinatorial Optimization 23rd European Conference, EvoCOP 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (pp.114-129). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-30035-6_8].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/502199
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