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Search results for: GENETIC ALGORITHMS, OPTIMIZATION METHODS, MATHEMATICAL PROGRAMMING, ELECTROMAGNETIC ANALYSIS
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Milena Marycz dr inż.
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Optymalizacja strategii sieci inteligentnych agentów za pomocą programowania genetycznego w systemie rozproszonym realizującym paradygmat volunteer computing
PublicationDynamicznie rosnąca złożoność i wymagania w odniesieniu do rozproszonych systemów informatycznych utrudnia zarządzanie dostępnymi zasobami sprzętowymi i programistycznymi. Z tego powodu celem rozprawy jest opracowanie wielokryterialnej metody programowania genetycznego, która pozwala na optymalizację strategii zespołu inteligentnych agentów programistycznych w zakresie zarządzania systemem realizującym paradygmat volunteer computing....
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Multimodal Genetic Algorithm with Phase Analysis to Solve Complex Equations of Electromagnetic Analysis
PublicationIn this contribution, a new genetic-algorithm-based method of finding roots and poles of a complex function of a complex variable is presented. The algorithm employs the phase analysis of the function to explore the complex plane with the use of the genetic algorithm. Hence, the candidate regions of root and pole occurrences are selected and verified with the use of discrete Cauchy's argument principle. The algorithm is evaluated...
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Genetic Programming with Negative Selection for Volunteer Computing System Optimization
PublicationVolunteer computing systems like BOINC or Comcute are strongly supported by a great number of volunteers who contribute resources of their computers via the Web. So, the high efficiency of such grid system is required, and that is why we have formulated a multi-criterion optimization problem for a volunteer grid system design. In that dilemma, both the cost of the host system and workload of a bottleneck host are minimized. On...
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Genetic Programming for Workload Balancing in the Comcute Grid System
PublicationA genetic programming paradigm is implemented for reliability optimization in the Comcute grid system design. Chromosomes are generated as the program functions and then genetic operators are applied for finding Pareto-suboptimal task assignment and scheduling. Results are compared with outcomes obtained by an adaptive evolutionary algorithm.
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Swarm Algorithms in Modern Engineering Optimization Problems
PublicationComplexity of today engineering problems is constantly increasing. Scientists no longer are facing issues, for which simple, mathematical programming methods are sufficient. Issues like autonomic vehicle navigation or classification are considered to be challenging, and although there exist valid means to solve them, in some cases there still is some place for improvement. With emergence of a new type of optimization techniques...
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Genetic Programming for Interaction Efficient Supporting in Volunteer Computing Systems
PublicationVolunteer computing systems provide a middleware for interaction between project owners and great number volunteers. In this chapter, a genetic programming paradigm has been proposed to a multi-objective scheduler design for efficient using some resources of volunteer computers via the web. In a studied problem, genetic scheduler can optimize both a workload of a bottleneck computer and cost of system. Genetic programming has been...
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Big Data Paradigm Developed in Volunteer Grid System with Genetic Programming Scheduler
PublicationArtificial intelligence techniques are capable to handle a large amount of information collected over the web. In this paper, big data paradigm has been studied in volunteer and grid system called Comcute that is optimized by a genetic programming scheduler. This scheduler can optimize load balancing and resource cost. Genetic programming optimizer has been applied for finding the Pareto solu-tions. Finally, some results from numerical...
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New approach to railway noise modeling employing Genetic Algorithms
PublicationMain goal of this paper was to describe an innovative method of noise prediction based on Genetic Algorithms. First part of the paper addresses the problem of growing noise, mainly in the context of a unified method for measuring noise. Further, Genetic Algorithms are described with regards to their fundamental features. Further a description is provided as to how Genetic Algorithms were used in the area of noise modeling. Next...
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Testing Stability of Digital Filters Using Optimization Methods with Phase Analysis
PublicationIn this paper, novel methods for the evaluation of digital-filter stability are investigated. The methods are based on phase analysis of a complex function in the characteristic equation of a digital filter. It allows for evaluating stability when a characteristic equation is not based on a polynomial. The operation of these methods relies on sampling the unit circle on the complex plane and extracting the phase quadrant of a function...