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Erschienen in: Soft Computing 2/2013

01.02.2013 | Focus

On user-centric memetic algorithms

verfasst von: Ana Reyes Badillo, Juan Jesús Ruiz, Carlos Cotta, Antonio J. Fernández-Leiva

Erschienen in: Soft Computing | Ausgabe 2/2013

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Abstract

Memetic algorithms (MAs) constitute a metaheuristic optimization paradigm [usually based on the synergistic combination of an evolutionary algorithm (EA) and trajectory-based optimization techniques] that systematically exploits the knowledge about the problem being solved and that has shown its efficacy to solve many combinatorial optimization problems. However, when the search depends heavily on human-expert’s intuition, the task of managing the problem knowledge might be really difficult or even indefinable/impossible; the so-called interactive evolutionary computation (IEC) helps to mitigate this problem by enabling the human user to interact with an EA during the optimization process. Interactive MAs can be constructed as reactive models in which the MA continuously demands the intervention of the human user; this approach has the drawback that provokes fatigue to the user. This paper considers user-centric MAs, a more global perspective of interactive MAs since it hints possibilities for the system to be proactive rather than merely interactive, i.e., to anticipate some of the user behavior and/or exhibit some degree of creativity, and provides some guidelines for the design of two different models for user-centric MAs, namely reactive and proactive search-based schema. An experimental study over two complex NP-hard problems, namely the Traveling Salesman problem and a Gene Ordering Problem, shows that user-centric MAs are in general effective optimization methods although the proactive approach provides additional advantages.

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Metadaten
Titel
On user-centric memetic algorithms
verfasst von
Ana Reyes Badillo
Juan Jesús Ruiz
Carlos Cotta
Antonio J. Fernández-Leiva
Publikationsdatum
01.02.2013
Verlag
Springer-Verlag
Erschienen in
Soft Computing / Ausgabe 2/2013
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-012-0893-6

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