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Exploration in stochastic algorithms: An application on MAX-MIN Ant System

Author

Listed:
  • Paola Pellegrini

    (Department of Applied Mathematics, University of Venice)

  • Elena Moretti

    (Department of Applied Mathematics, University of Venice)

  • Daniela Favaretto

    (Department of Applied Mathematics, University of Venice)

Abstract

In this paper a definition of the exploration performed by stochastic algorithms is proposed. It is based on the observation through cluster analysis of the solutions generated during a run. The probabilities associated by an algorithm to solution components are considered. Moreover, a consequent method for quantifying the exploration is provided. Such a measurement is applied to MAX-MIN Ant System. The results of the experimental analysis allow to observe the impact of the parameters of the algorithm on the exploration.

Suggested Citation

  • Paola Pellegrini & Elena Moretti & Daniela Favaretto, 2008. "Exploration in stochastic algorithms: An application on MAX-MIN Ant System," Working Papers 169, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    • Handle: RePEc:vnm:wpaper:169
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    File URL: http://virgo.unive.it/wpideas/storage/2008wp169.pdf
    File Function: First version, 2008
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    References listed on IDEAS

    as
    1. Walter J. Gutjahr & Giovanni Sebastiani, 2008. "Runtime Analysis of Ant Colony Optimization with Best-So-Far Reinforcement," Methodology and Computing in Applied Probability, Springer, vol. 10(3), pages 409-433, September.
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    More about this item

    Keywords

    exploration; cluster analysis; MAX-MIN Ant System;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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