E. Stanevičienė “The application of hybrid genetical algoriths for the grey pattern problem” doctoral dissertation defence

Author, Institution: Evelina Stanevičienė, Kaunas University of Technology

Science area, field of science: Natural Sciences, Informatics, N 009

Scientific Supervisor: Prof. Dr. Alfonsas Misevičius (Kaunas University of Technology, Natural Sciences, Informatics, N 009)

Dissertation Defence Board of Natural Sciences Field:
Prof. Dr. Habil. Rimantas Barauskas (Kaunas University of Technology, Natural Sciences, Informatics, N 009) – chairman,
Prof. Dr. Habil. Gintautas Dzemyda (Vilnius University, Natural Sciences, Informatics, N 009),
Prof. Dr. Vacius Jusas (Kaunas University of Technology, Natural Sciences, Informatics, N 009).
Prof. Dr. Gintaras Palubeckis (Kaunas University of Technology, Natural Sciences, Informatics, N 009),
Prof. Dr. Raimund Ubar (Tallinn University of Technology, Estonia,  Natural Sciences, Informatics – N 009).

The doctoral dissertation is available at the libraries of Kaunas University of Technology (K. Donelaičio g. 20, 44239 Kaunas), Vytautas Magnus University (K. Donelaičio g. 52, Kaunas) and Vilnius Gediminas Technical University (Saulėtekio al. 14, 10223 Vilnius).

Annotation:

The aim of the research is to investigate the effectiveness of hybrid genetic algorithm modifications for the grey pattern problem and to determine the most effective algorithm variants. The object of the research is the hybrid genetic algorithms for the grey pattern problem.
Scientific novelty is that the hybrid genetic algorithm of an improved structure (architecture) was proposed for the grey pattern problem. The hybrid genetic algorithm was implemented with a new type of integrated iterative tabu search procedure combined with the efficient adaptive perturbation of solutions.
The hybrid genetic algorithm was successfully applied to the grey pattern quadratic assignment problem, which is utilized as a formal model for construction of the digital halftones.