Multiobjective Adaptive Metaheuristics

Mirialys Machin Navas, Antonio J. Nebro Urbaneja


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.


Adaptive strategy, metaheuristics, multiobjective optimization.

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