Swinburne
Browse

Solving problems with hidden dynamics: comparison of extremal optimisation and ant colony system

Download (156.25 kB)
conference contribution
posted on 2024-07-12, 11:59 authored by I. Moser, Tim HendtlassTim Hendtlass
Solving dynamic combinatorial problems poses a particular challenge to optimisation algorithms. Optimising a dynamic problem that does not notify the solver when a change has been made is very difficult for most well-known algorithms. Extremal Optimisation is a recent addition to the group of biologically inspired optimisation algorithms, while Ant Colony System has been used to solve a large variety of problem types in static and dynamic contexts. Both algorithms seem well suited to solving problems with hidden dynamics. We present a performance comparison of the two algorithms and endeavour to highlight particular strengths and weaknesses observed with different types of dynamic problem changes.

History

Available versions

PDF (Published version)

ISBN

9780780394872

Journal title

2006 IEEE Congress on Evolutionary Computation (CEC 2006) Vancouver, British Columbia, Canada, 16-21 July 2006

Conference name

2006 IEEE Congress on Evolutionary Computation CEC 2006 Vancouver, British Columbia, Canada, 16-21 July 2006

Pagination

7 pp

Publisher

IEEE

Copyright statement

Copyright © 2006 IEEE. Paper is reproduced in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in oTher works must be obtained from The IEEE.

Language

eng

Usage metrics

    Publications

    Categories

    No categories selected

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC