Comparison and Selection of Exact and Heuristic Algorithms

  • Joaquín Pérez O.
  • Rodolfo A. Pazos R.
  • Juan Frausto S.
  • Guillermo Rodríguez O.
  • Laura Cruz R.
  • Héctor Fraire H.
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3045)

Abstract

The traditional approach for comparing heuristic algorithms uses well-known statistical tests for meaningfully relating the empirical performance of the algorithms and concludes that one outperforms the other. In contrast, the method presented in this paper, builds a predictive model of the algorithms behavior using functions that relate performance to problem size, in order to define dominance regions. This method generates first a representative sample of the algorithms performance, then using a common and simplified regression analysis determines performance functions, which are finally incorporated into an algorithm selection mechanism. For testing purposes, a set of same-class instances of the database distribution problem was solved using an exact algorithm (Branch&Bound) and a heuristic algorithm (Simulated Annealing). Experimental results show that problem size affects differently both algorithms, in such a way that there exist regions where one algorithm is more efficient than the other.

Keywords

Migration 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Joaquín Pérez O.
    • 1
  • Rodolfo A. Pazos R.
    • 1
  • Juan Frausto S.
    • 2
  • Guillermo Rodríguez O.
    • 3
  • Laura Cruz R.
    • 4
  • Héctor Fraire H.
    • 4
  1. 1.Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET)CuernavacaMéxico
  2. 2.ITESMCampus Cuernavaca, MéxicoCuernavacaMéxico
  3. 3.Instituto de Investigaciones EléctricasIIE 
  4. 4.Instituto Tecnológico de Ciudad MaderoMéxico

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