MODELING OF TECHNOLOGICAL SYSTEMS BY THE USE OF GENETIC METHODS

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@PhdThesis{Brezocnik:thesis,

• author = "Miran Brezocnik",
• title = "MODELING OF TECHNOLOGICAL SYSTEMS BY THE USE OF GENETIC METHODS",
• school = "University of Maribor, Faculty of Mechanical Engineering",
• year = "1998",
• type = "phdthesis",
• address = "Smetanova ulica 17, SI-2000 Maribor, Slovenia",
• email = "mbrezocnik@uni-mb.si",
• keywords = "genetic algorithms, genetic programming, intelligent manufacturing systems, technological system, forming, assembly, robots, self-organisation, genetic methods, modelling, optimisation",
• size = "129 pages",
• abstract = "In this work we propose modelling of different technological systems by a general approach. The research starts with searching for common characteristics of the technological systems. After they have been found out, they are synthesised into uniform principle serving for conceiving a general method for their modeling. The method imitates associating of living cells into tissues, organs and organisms. The disturbances resulting from limited human knowledge, unpredictability of technological systems, and unexpected events in production environment are automatically eliminated during the evolutionary process. More and more intelligent behaviour of the individual technological system, which is expressed as an increasingly successful synchronisation of the material, energy and information, is obtained gradually with self-organization and without centralised instruction.

  In order to support the theoretical researches a system for genetic programming is developed. It is successfully used for genetic modeling of: 1. forming efficiency, 2. assembly and classification, and 3. trajectories of robots in the production environment. The results of modeling of forming efficiency show excellent correspondence between analytically obtained models, experimental results, and genetically developed models. In case of genetic modeling of assembly the basic components are integrated into the final product in a self-organising manner. Genetic modelling the trajectory of the robot, striving to arrive at the aim through a dynamic production environment, discovers the intelligent robot navigation formed during the evolutionary process.",

}

Genetic Programming entries for Miran Brezocnik

Citations