Computational Science Technical Note CSTN-190

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Visualisation of Combinatorial Program Space and Related Metrics

Alwyn V. Husselmann and K. A. Hawick

Archived: 2013

Abstract

Searching a large knowledge or information space for optimal regions demands sophisticated algorithms, and sometimes unusual hybrids or combined algorithms. Choosing the best algorithm often requires obtaining a good intuitive or visual understanding of its properties and progress through a space. Visualisation in combinatorial optimizers is more challenging than visualising parametric optimizers. Each problem in combinatorial optimisation is qualitative and has a very different objective, whereas parametric optimizers are quantitative and can be visualised almost trivially. We present a method for visualising abstract syntax trees in an interactive manner, as well as some certain enhancements for evolutionary algorithms. We also discuss the use of this in improving the convergence performance of a Geometric Particle Swarm Optimiser.

Keywords: combinatorial information; knowledge engineering; visualisation, genetic programming, optimization

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@INPROCEEDINGS{CSTN-190,
        author = {Alwyn V. Husselmann and K. A. Hawick},
        title = {Visualisation of Combinatorial Program Space and Related Metrics},
        booktitle = {Proc. 12th International Conference on Information and Knowledge
                Engineering (IKE'13)},
        year = {2013},
        number = {CSTN-190},
        pages = {IKE3096},
        address = {Las Vegas, USA},
        month = {22-25 July},
        publisher = {WorldComp},
        institution = {Computer Science, Massey University, Auckland, New Zealand},
        keywords = {combinatorial information; knowledge engineering; visualisation, genetic
                programming, optimization},
        owner = {kahawick},
        timestamp = {2013.03.19}
}


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