Minimum Addition Chains Generation Using Evolutionary Strategies



Título del documento: Minimum Addition Chains Generation Using Evolutionary Strategies
Revista: Computación y sistemas
Base de datos:
Número de sistema: 000560387
ISSN: 1405-5546
Autores: 1
1
1
1
2
3
Instituciones: 1Instituto Politécnico Nacional, Centro de Innovación y Desarrollo Tecnológico en Cómputo, Ciudad de México. México
2Universidad Tecnológica de México, Ciudad de México. México
3Instituto Politécnico Nacional, Ciudad de México. México
Año:
Periodo: Oct-Dic
Volumen: 22
Número: 4
Paginación: 1463-1472
País: México
Idioma: Inglés
Tipo de documento: Artículo
Resumen en inglés The calculus for a power of a number could be a time and computational cost-consuming task. A method for reducing this issue is welcome in all mayor computational areas as cryptography, numerical series and elliptic curves calculus, just to mention a few. This paper details the development of a minimum length addition chains generator based on an Evolutionary Strategy, which makes fewer calls to the objective function with respect to other proposals that also use bio-inspirated algorithms as Particle Swarm Optimization or a Genetic Algorithm. By using fewer calls to the objective function, the number of calculations is lower and consequently decreases the generation time providing an improvement in computational cost but obtaining competitive results.
Disciplinas: Ciencias de la computación
Palabras clave: Inteligencia artificial
Keyword: Minimum length,
Addition chains,
Evolutionary strategy,
Computational cost reduction,
Artificial intelligence
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