The networked evolutionary algorithm : A network science perspective

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

46 Scopus Citations
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Author(s)

  • Wenbo Du
  • Mingyuan Zhang
  • Wen Ying
  • Matjaž Perc
  • Ke Tang
  • Xianbin Cao

Detail(s)

Original languageEnglish
Pages (from-to)33-43
Journal / PublicationApplied Mathematics and Computation
Volume338
Publication statusPublished - 1 Dec 2018
Externally publishedYes

Abstract

The evolutionary algorithm is one of the most popular and effective methods to solve complex non-convex optimization problems in different areas of research. In this paper, we systematically explore the evolutionary algorithm as a networked interaction system, where nodes represent information process units and connections denote information transmission links. Within this networked evolutionary algorithm framework, we analyze the effects of structure and information fusion strategies, and further implement it in three typical evolutionary algorithms, namely in the genetic algorithm, the particle swarm optimization algorithm, and in the differential evolution algorithm. Our results demonstrate that the networked evolutionary algorithm framework can significantly improve the performance of these evolutionary algorithms. Our work bridges two traditionally separate areas, evolutionary algorithms and network science, in the hope that it promotes the development of both.

Research Area(s)

  • Behavior, Evolutionary algorithm, Network system, Structure

Bibliographic Note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to lbscholars@cityu.edu.hk.

Citation Format(s)

The networked evolutionary algorithm : A network science perspective. / Du, Wenbo; Zhang, Mingyuan; Ying, Wen; Perc, Matjaž; Tang, Ke; Cao, Xianbin; Wu, Dapeng.

In: Applied Mathematics and Computation, Vol. 338, 01.12.2018, p. 33-43.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review