Ambidextrous Socio-Cultural Algorithms

José Lemus-Romani, BRODERICK CRAWFORD LABRIN, RICARDO JAVIER SOTO DE GIORGIS, Gino Astorga, Sanjay Misra, Kathleen Crawford, Giancarla Foschino, Agustín Salas-Fernández, Fernando Paredes

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Metaheuristics are a class of algorithms with some intelligence and self-learning capabilities to find solutions to difficult combinatorial problems. Although the promised solutions are not necessarily globally optimal, they are computationally economical. In general, these types of algorithms have been created by imitating intelligent processes and behaviors observed in nature, sociology, psychology and other disciplines. Metaheuristic-based search and optimization is currently widely used for decision making and problem solving in different contexts. The inspiration for metaheuristic algorithms are mainly based on nature’s behaviour or biological behaviour. Designing a good metaheurisitcs is making a proper trade-off between two forces: Exploration and exploitation. It is one of the most basic dilemmas that both individuals and organizations constantly are facing. But there is a little researched branch, which corresponds to the techniques based on the social behavior of people or communities, which are called Social-inspired. In this paper we explain and compare two socio-inspired metaheuristics solving a benchmark combinatorial problem.

Idioma originalInglés
Título de la publicación alojadaComputational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings
EditoresOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blecic, David Taniar, Bernady O. Apduhan, Ana Maria A.C. Rocha, Eufemia Tarantino, Carmelo Maria Torre, Yeliz Karaca
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas923-938
Número de páginas16
ISBN (versión impresa)9783030588168
DOI
EstadoPublicada - 2020
Publicado de forma externa
Evento20th International Conference on Computational Science and Its Applications, ICCSA 2020 - Cagliari, Italia
Duración: 1 jul 20204 jul 2020

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen12254 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia20th International Conference on Computational Science and Its Applications, ICCSA 2020
País/TerritorioItalia
CiudadCagliari
Período1/07/204/07/20

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