SciELO - Scientific Electronic Library Online

 
vol.14 issue1An Efficient Δ-Causal Distributed Algorithm for Synchronous Cooperative Systems in Unreliable NetworksIs the Coordinated Clusters Representation an analog of the Local Binary Pattern? author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

Print version ISSN 1405-5546

Abstract

FRAIRE HUACUJA, Héctor Joaquín et al. Reducing the Experiments Required to Assess the Performance of Metaheuristic. Comp. y Sist. [online]. 2010, vol.14, n.1, pp.44-53. ISSN 1405-5546.

When assessing experimentally the performance of metaheuristic algorithms on a set of hard instances of an NP-complete problem, the required time to carry out the experimentation can be very large. A means to reduce the needed effort is to incorporate variance reduction techniques in the computational experiments. For the incorporartion of these techniques, the traditional approaches propose methods which depend on the technique, the problem and the metaheuristic algorithm used. In this work we develop general-purpose methods, which allow incorporating techniques of variance reduction, independently of the problem and of the metaheuristic algorithm used. To validate the feasibility of the approach, a general-purpose method is described which allows incorporating the antithetic variables technique in computational experiments with randomized metaheuristic algorithms. Experimental evidence shows that the proposed method yields a variance reduction of the random outputs in 78% and that the method has the capacity of simultaneously reducing the variance of several random outputs of the algorithms tested. The overall reduction levels reached on the instances used in the test cases lie in the range from 14% to 55%.

Keywords : Experimental algorithm analysis; variance reduction techniques and metaheuristic algorithms.

        · abstract in Spanish     · text in English     · English ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License