RT Journal Article
T1 Bio-inspired computation: 												Where we stand and what's next
A1 Del Ser, Javier
A1 Osaba, Eneko
A1 Molina, Daniel
A1 Yang, Xin She
A1 Salcedo-Sanz, Sancho
A1 Camacho, David
A1 Das, Swagatam
A1 Suganthan, Ponnuthurai N.
A1 Coello Coello, Carlos A.
A1 Herrera, Francisco
AB 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.
SN 2210-6502
YR 2019
FD 2019-08
LA eng
NO Del Ser , J , Osaba , E , Molina , D , Yang , X S , Salcedo-Sanz , S , Camacho , D , Das , S , Suganthan , P N , Coello Coello , C A & Herrera , F 2019 , ' Bio-inspired computation : Where we stand and what's next ' , Swarm and Evolutionary Computation , vol. 48 , pp. 220-250 . https://doi.org/10.1016/j.swevo.2019.04.008
NO Publisher Copyright: © 2019 Elsevier B.V.
NO Javier Del Ser and Eneko Osaba would like to thank the Basque Government for funding support received through the EMAITEK and ELKARTEK funding programs. The work of Sancho Salcedo-Sanz and David Camacho is partially supported by the Ministerio de Economía y Competitividad (MINECO)of Spain (grant no. TIN2017-85887-C2-2-P and TIN2017-85727-C4-3-P, respectively). The work of Daniel Molina and Francisco Herrera is supported by the Spanish Ministry of Science (grants TIN2016-8113-R and TIN2017-89517-P). Carlos A. Coello Coello acknowledges support from CONACYT grant no. 2016-01-1920 (Investigación en Fronteras de la Ciencia 2016). Javier Del Ser would also like to thank Prof. Josu Ceberio from the University of the Basque Country (UPV/EHU)and Dr. Esther Villar-Rodriguez from TECNALIA for fruitful discussions that improved this manuscript. All the authors are grateful to the anonymous reviewers for their insightful feedback. Javier Del Ser and Eneko Osaba would like to thank the Basque Government for funding support received through the EMAITEK and ELKARTEK funding programs. The work of Sancho Salcedo-Sanz and David Camacho is partially supported by the Ministerio de Economía y Competitividad (MINECO) of Spain (grant no. TIN2017-85887-C2-2-P and TIN2017-85727-C4-3-P , respectively). The work of Daniel Molina and Francisco Herrera is supported by the Spanish Ministry of Science (grants TIN2016-8113-R and TIN2017-89517-P ). Carlos A. Coello Coello acknowledges support from CONACYT grant no. 2016-01-1920 (Investigación en Fronteras de la Ciencia 2016). Javier Del Ser would also like to thank Prof. Josu Ceberio from the University of the Basque Country (UPV/EHU) and Dr. Esther Villar-Rodriguez from TECNALIA for fruitful discussions that improved this manuscript. All the authors are grateful to the anonymous reviewers for their insightful feedback.
DS TECNALIA Publications
RD 28 jul 2024