Multivariate cauchy EDA optimisation

Momodou L. Sanyang, Ata Kaban

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


We consider Black-Box continuous optimization by Estimation of Distribution Algorithms (EDA). In continuous EDA, the multivariate Gaussian distribution is widely used as a search operator, and it has the well-known advantage of modelling the correlation structure of the search variables, which univariate EDA lacks. However, the Gaussian distribution as a search operator is prone to premature convergence when the population is far from the optimum. Recent work suggests that replacing the univariate Gaussian with a univariate Cauchy distribution in EDA holds promise in alleviating this problem because it is able to make larger jumps in the search space due to the Cauchy distribution's heavy tails. In this paper, we propose the use of a multivariate Cauchy distribution to blend together the advantages of multivariate modelling with the ability of escaping early convergence to efficiently explore the search space. Experiments on 16 benchmark functions demonstrate the superiority of multivariate Cauchy EDA against univariate Cauchy EDA, and its advantages against multivariate Gaussian EDA when the population lies far from the optimum.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning
Subtitle of host publicationIDEAL 2014 15th International Conference, Salamanca, Spain, September 10-12, 2014. Proceedings
EditorsEmilio Corchado, José A. Lozano , Héctor Quintián , Hujun Yin
Number of pages8
Volume8669 LNCS
ISBN (Electronic)9783319108407
ISBN (Print)9783319108391
Publication statusPublished - 2014
Event15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014 - Salamanca, Spain
Duration: 10 Sept 201412 Sept 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8669 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349


Conference15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014


  • Black-box Optimization
  • Estimation of Distribution Algorithm
  • Multivariate Cauchy Distribution
  • Multivariate Gaussian distribution

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science


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