SciELO - Scientific Electronic Library Online

 
vol.17 issue1Feature Selection using Associative Memory Paradigm and Parallel ComputingA Novel Approach for Pseudo-Random Seed Generation 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

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

MACHIN NAVAS, Mirialys  and  NEBRO URBANEJA, Antonio J.. Multiobjective Adaptive Metaheuristics. Comp. y Sist. [online]. 2013, vol.17, n.1, pp.53-62. ISSN 2007-9737.

Solution of Abstract Optimization problems with two or more conflicting functions or objectives by using metaheuristics has attracted attention of researches and become a rapidly developing area known as Multiobjective Optimization. Metaheuristics are non-exact techniques aimed to produce satisfactory solutions to complex optimization problems where exact techniques are not applicable; they are characterized by using some operators that are applied in a stochastic way according to a given parameterization. The settings of these parameters are usually established at the beginning of the execution of algorithms, and they remain unchanged until the search finishes. Recently, a number of papers studying adaptive modifications of these parameters on the fly have emerged. In this work, we report a study of the effect of using two operators in an adaptive way in two multiobjective metaheuristics representative of the state-of-the-art. The obtained results demonstrate that it is possible to improve the search performance of two chosen algorithms by using the adaptive scheme.

Keywords : Adaptive strategy; metaheuristics; multiobjective optimization.

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

 

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