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Bio-inspired computation: Where we stand and what's next

  • Javier Del Ser*
  • , Eneko Osaba
  • , Daniel Molina
  • , Xin She Yang
  • , Sancho Salcedo-Sanz
  • , David Camacho
  • , Swagatam Das
  • , Ponnuthurai N. Suganthan
  • , Carlos A. Coello Coello
  • , Francisco Herrera
  • *Autor correspondiente de este trabajo
  • Basque Center for Applied Mathematics
  • University of Granada
  • Middlesex University
  • University of Alcalá
  • Universidad Autónoma de Madrid
  • Indian Statistical Institute
  • Nanyang Technological University
  • Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

548 Citas (Scopus)

Resumen

In recent years, the research community has witnessed an explosion of literature dealing with the mimicking of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others. Notwithstanding this upsurge of activity, research in this vibrant topic should be steered towards certain areas that, despite their eventual value and impact on the field of bio-inspired computation, still remain insufficiently explored to date. The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization. An analysis and discussion are also carried out over the general trajectory followed in recent years by the community working in this field, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques.

Idioma originalInglés
Páginas (desde-hasta)220-250
Número de páginas31
PublicaciónSwarm and Evolutionary Computation
Volumen48
DOI
EstadoPublicada - ago 2019

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

  1. ODS 9: Industria, innovación e infraestructura
    ODS 9: Industria, innovación e infraestructura

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