Evolutionary diffusion optimization, Part II: Performance assessment

Kwok Ching Tsui, Jiming LIU

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

A new population-based stochastic search algorithm called evolutionary diffusion optimization (EDO) inspired by diffusion in nature has been proposed. This article compares the performance of EDO with simulated annealing and fast evolutionary programming. Experimental results show that EDO performs better than SA and FEP in some cases.

Original languageEnglish
Title of host publicationProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002
PublisherIEEE Computer Society
Pages1284-1289
Number of pages6
ISBN (Print)0780372824, 9780780372825
DOIs
Publication statusPublished - 2002
Event2002 Congress on Evolutionary Computation, CEC 2002 - Honolulu, HI, United States
Duration: 12 May 200217 May 2002

Publication series

NameProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002
Volume2

Conference

Conference2002 Congress on Evolutionary Computation, CEC 2002
Country/TerritoryUnited States
CityHonolulu, HI
Period12/05/0217/05/02

Scopus Subject Areas

  • Software

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