Non-uniform mode-pursuing sampling method based on multivariate multimodal distribution model

Hua Su, Liangxian Gu, Chunlin Gong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A non-uniform distributing based mode-pursuing sampling method on black-box problem is proposed for the computation-intensive global optimization problem. The multivariate multimodal distribution model is established based on the expensive sample points of original optimization problem, which is controlled by the convergence principle of multiple correlation coefficient through variance of probability distribution. More design points are generated progressively around the current optimal regions and constitute the non-uniform discrete design space. Non-uniform sampling strategy changes the uniform distributing characteristic of design space, improves the utilization efficiency of design points and strengthens the distribution rationality of discrete design space. Analytical and numerical test results show that the improved method is more efficient and accurate than standard mode-pursuing sampling method and traditional algorithms, and has broad prospects for the expensive black-box problem.

Original languageEnglish
Title of host publication2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012
Pages309-313
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012 - Nanjing, China
Duration: 18 Oct 201220 Oct 2012

Publication series

Name2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012

Conference

Conference2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012
Country/TerritoryChina
CityNanjing
Period18/10/1220/10/12

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