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EMAS in Optimization Problems

  • Aleksander ByrskiEmail author
  • Marek Kisiel-Dorohinicki
Chapter
  • 589 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 680)

Abstract

Considering the “no free lunch theorem” (Wolpert and Macready, IEEE Trans Evolut Comput 67(1), 1997, [297]), it is still important to try to test how the examined metaheuristic works when applied to different well-known problems. That is why several well-known benchmark functions are considered in the following experimental study (Digalakis and Margaritis, Int J Comput Math 79(4):403–416, 2002, [82]). In order to obtain plausible results, the systems compared should be parametrized in the most similar way. So it is the case presented in this section, as EMAS, and its memetic variants (Baldwinian and Lamarckian) are compared with PEA (along with respective memetic modifications). Later, a comparison between EMAS and its immunological variant (iEMAS) is made. Finally two discrete problems are tackled: Low Autocorrelation Binary Sequence (LABS) and Optimal Golomb Ruler (OGR).

Keywords

Fitness Function Local Extremum Benchmark Function Fitness Function Evaluation Ising Spin Glass 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Computer Science, Electronics and Telecommunications, Department of Computer ScienceAGH University of Science and TechnologyKrakówPoland

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