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1
Content available Evolutionary computation approaches to tip position controller design for a two-link flexible manipulator
100%
Subudhi B. , Ranasingh S. , Swain A. K.
Archives of Control Sciences
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2011
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tom Vol. 21, no. 3
269-285
EN
Controlling multi-link flexible robots is very difficult compared rigid ones due to inter-link coupling, nonlinear dynamics, distributed link flexure and under-actuation. Hence, while designing controllers for such systems the controllers should be equipped with optimal gain parameters. Evolutionary Computing (EC) approaches such as Genetic Algorithm (GA), Bacteria Foraging Optimization (BFO) are popular in achieving global parameter optimizations. In this paper we exploit these EC techniques in achieving optimal PD controller for controlling the tip position of a two-link flexible robot. Performance analysis of the EC tuned PD controllers applied to a two-link flexible robot system has been discussed with number of simulation results.
2
Content available Hybrid Mesh Adaptive Direct Search and Genetic Algorithms Techniques for industrial production systems
88%
Vasant P.
Archives of Control Sciences
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2011
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tom Vol. 21, no. 3
299-312
EN
In this paper, computational and simulation results are presented for the performance of the fitness function, decision variables and CPU time of the proposed hybridization method of Mesh Adaptive Direct Search (MADS) and Genetic Algorithm (GA). MADS is a class of direct search of algorithms for nonlinear optimization. The MADS algorithm is a modification of the Pattern Search (PS) algorithm. The algorithms differ in how the set of points forming the mesh is computed. The PS algorithm uses fixed direction vectors, whereas the MADS algorithm uses random selection of vectors to define the mesh. A key advantage of MADS over PS is that local exploration of the space of variables is not restricted to a finite number of directions (poll directions). This is the primary drawback of PS algorithms, and therefore the main motivation in using MADS to solve the industrial production planning problem is to overcome this restriction. A thorough investigation on hybrid MADS and GA is performed for the quality of the best fitness function, decision variables and computational CPU time.
3
Content available remote A Parallel Genetic Algorithm for Creating Virtual Portraits of Historical Figures
88%
Krawczyk H. , Proficz J. , Ziółkowski T.
TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk
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2012
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tom Vol. 16, No 1-2
145-162
EN
In this paper we present a genetic algorithm (GA) for creating hypothetical virtual portraits of historical figures and other individuals whose facial appearance is unknown. Our algorithm uses existing portraits of random people from a specific historical period and social background to evolve a set of face images potentially resembling the person whose image is to be found. We then use portraits of the person’s relatives to judge which of the evolved images are most likely to resemble his/her actual appearance. Unlike typical GAs, our algorithm uses a new supervised form of fitness function which itself is affected by the evolution process. Additional description of requested facial features can be provided to further influence the final solution (i.e. the virtual portrait). We present an example of a virtual portrait created by our algorithm. Finally, the performance of a parallel implementation developed for the KASKADA platform is presented and evaluated.
4
Wpływ parametrów funkcji celu na dobór nastaw okresów w elastycznym modelu szeregowania zadań
75%
Powroźnik P.
Studia Informatica
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2012
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tom Vol. 33, nr 3A
101-110
PL
Elastyczny model szeregowania zadań umożliwia zapewnienie warunku realizowalności zadań w węźle systemu pomiarowo - sterującego, w którym występują zadania aperiodyczae lub periodyczne, zmieniające swoje parametry czasowe. W elastycznym modelu algorytmy heurystyczne poszukają i oceniają nowe dobory okresów zadań za pomocą funkcji celu. W artykule przedstawiono wyniki badań symulacyjnych sprawdzające poprawność opracowanej funkcji celu.
EN
Elastic task model scheduling allows to ensnre reliability condition for node that has aperiodic and periodic tasks changing their tiining parameters. ln this model heuristic algorithms seek and evaluate new periods of tasks with fitness function. This paper presents the results of simulation studies validate the developed fitness functions.
5
Learning rule structures of fuzzy controllers based on genetic algorithm.
75%
Xiong N.
Systems Science
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2000
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tom Vol. 26, nr 2
69-84
EN
One of the major difficulties in fuzzy control of complex processes is the "curse of dimensionality". For the sake of a reduced size of the knowledge base some rules with incomplete premise structures covering larger regions of input domain are often desirable. The paper presents a genetic algorithm based approach to searching for suitable antecedents under which specific fuzzy actions could be derived. The rule premises are coded in a flexible way allowing the presence as well as absence of an input variable in them, in combination with a certain class of input and output fuzzy sets. On the other hand, a consistency index is introduced to give a numerical evaluation of the coherence among individual rules. This index is incorporated into the fitness function of the genetic algorithm to search for a set of optimal rule premises yielding not only good control performances but also little conflict in the rule base. The effectiveness of our work is demonstrated through experiment results on an inverted pendulum.
6
Content available remote Experimental Research on Evolutionary Path Planning Algorithm with Fitness Function Scaling for Collision Scenarios
75%
Kolendo P. , Smierzchalski R. , Jaworski B.
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
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2011
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tom Vol. 5, no. 4
489--495
EN
This article presents typical ship collision scenarios, simulated using the evolutionary path planning system and analyses the impact of the fitness function scaling on the quality of the solution. The function scaling decreases the selective pressure, which facilitates leaving the local optimum in the calculation process and further exploration of the solution space. The performed investigations have proved that the use of scaling in the evolutionary path planning method makes it possible to preserve the diversity of solu-tions by a larger number of generations in the exploration phase, what could result in finding better solution at the end. The problem of avoiding collisions well fitted the algorithm in question, as it easily incorporates dynamic objects (moving ships) into its simulations, however the use scaling with this particular problem has proven to be redundant.
7
Content available Pragmatic Distribution Based Routing Cluster to Improve Energy Efficient Cluster lifetime for Wireless Sensor Networks
75%
SV H. , NV A.
International Journal of Electronics and Telecommunications
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2023
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tom Vol. 69, No. 2
353--360
EN
Energy consumed by the sensor nodes are more sporadic in a sensor networks. A skilled way to bring down energy consumption and extend maximum life-time of any sensor present can be of evenly and unevenly distributed random area networks. Cluster heads are more responsible for the links between the source and destination. Energy consumption are much compare to member nodes of the network. Re-clustering will take place if the connectivity in the distributed network failure occurs in between the cluster networks that will affects redundancy in the network efficiency. Hence, we propose pragmatic distribution based routing cluster lifetime using fitness function (PDBRC) prototype is better than the existing protocol using MATLAB 2021a simulation tool.
8
Content available Optimization of thermo-electric coolers using hybrid genetic algorithm and simulated annealing
75%
Khanh D. V. K. , Vasant P. , Elamvazuthi I. , Dieu V. N.
Archives of Control Sciences
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2014
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tom Vol. 24, no. 2
155--176
EN
Thermo-electric Coolers (TECs) nowadays are applied in a wide range of thermal energy systems. This is due to their superior features where no refrigerant and dynamic parts are needed. TECs generate no electrical or acoustical noise and are environmentally friendly. Over the past decades, many researches were employed to improve the efficiency of TECs by enhancing the material parameters and design parameters. The material parameters are restricted by currently available materials and module fabricating technologies. Therefore, the main objective of TECs design is to determine a set of design parameters such as leg area, leg length and the number of legs. Two elements that play an important role when considering the suitability of TECs in applications are rated of refrigeration (ROR) and coefficient of performance (COP). In this paper, the review of some previous researches will be conducted to see the diversity of optimization in the design of TECs in enhancing the performance and efficiency. After that, single-objective optimization problems (SOP) will be tested first by using Genetic Algorithm (GA) and Simulated Annealing (SA) to optimize geometry properties so that TECs will operate at near optimal conditions. Equality constraint and inequality constraint were taken into consideration.
9
Content available Short-term load prediction model combining FEW and IHS algorithm
75%
Yu M. , Zhu J. , Yang L.
Archives of Electrical Engineering
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2019
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tom Vol. 68, nr 4
907--923
EN
:Accurate prediction of power load plays a crucial role in the power industry and provides economic operation decisions for the power operation department. Due to the unpredictability and periodicity of power load, an improved method to deal with complex nonlinear relation was adopted, and a short-term load forecasting model combining FEW (fuzzy exponential weighting) and IHS (improved harmonic search) algorithms was proposed. Firstly, the domain space was defined, the harmony memory base was initialized, and the fuzzy logic relation was identified. Then the optimal interval length was calculated using the training sample data, and local and global optimum were updated by optimization criteria and judging criteria. Finally, the optimized parameters obtained by an IHS algorithm were applied to the FEW model and the load data of the Huludao region (2013) in Northeast China in May. The accuracy of the proposed model was verified using an evaluation criterion as the fitness function. The results of error analysis show that the model can effectively predict short-term power load data and has high stability and accuracy, which provides a reference for application of short-term prediction in other industrial fields.
10
Content available remote Heavy loading conditions studies by optimal UPFC on a real Finnish 110 KV network to solve technical problems of 2020
75%
Othman A. , Lehtonen M. , El-Arini M.
Przegląd Elektrotechniczny
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2010
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tom R. 86, nr 11a
23-27
EN
Unified Power Flow Controller (UPFC) has effective options to deal with most of the technical problems in the power system operation. This ability gives to UPFC the power to control the voltage profile and the transmission lines flow simultaneously. In this paper, we define the optimal locations and settings of UPFC using the Genetics Algorithm (GA) to solve real technical problems in a real Finnish network, Helsinki HELENSÄHKÖVERKKO OY 110 KV NETWORK, specially solving the transmission lines overloading at heavy loading operations of Year 2020.
PL
Unified Power Flow Controller (UPFC) ma możliwości skutecznego rozwiązywania większości problemów technicznych w funkcjonowaniu systemu elektroenergetycznego. Ta umiejętność istnieje dzięki kontroli napięcia i przepływu linii przesyłowych jednocześnie. W niniejszej pracy określono optymalną lokalizację i ustawienia UPFC za pomocą algorytmu genetycznego (GA) do rozwiązywania rzeczywistych problemów technicznych w rzeczywistej sieci fińskiej, sieci Helsinki HELENSÄHKÖVERKKO OY 110 kV, pokazano specjalne rozwiązania wobec przeciążenia linii przesyłowych spodziewanych w 2020 roku.
11
Ewolucyjny projektant filtrów
63%
Golonek T. , Fedrizzi S. , Grzechca D.
Elektronika : konstrukcje, technologie, zastosowania
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2007
|
tom Vol. 48, nr 11
58-61
PL
Zaprezentowano ewolucyjną metodę projektowania filtrów analogowych. Synteza filtru opiera się na systemie programowania genetycznego, który minimalizuje średniokwadratowy błąd charakterystyki amplitudowej fenotypu. Podczas ewolucji optymalizowane są: konfiguracja połączeń obwodu i wartości stałych układowych (tj. pojemności kondensatorów, indukcyjności cewek i rezystancji rezystorów). Transmitancja filtru oraz jego struktura kodowane są przy wykorzystaniu elementarnych bloków czwórnikowych RC, RL i impedancyjnych, admitancyjnych oraz łańcuchowych równań charakterystycznych.
EN
The evolutionary method of analog filter design is proposed in this paper. Filter synthesis is based on genetic programming system with the minimization of mean square error amplitude response for phe-notypes. During evolution, both the analog filter circuit configuration and circuit contant values (i.e. capacitances, inductances and resistances) are optimized. The filter transmit function and its structure are coded with the use of tree-terminal elementary RC, RL blocks described by their impedance, conductance and chain matrices.
12
A genetic algorithm for automatic map symbols placement
63%
Bartonek D.
Electronic Journal of Polish Agricultural Universities. Series: Geodesy and Cartography
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2003
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tom 06
|
nr 1
EN
Genetic algorithms represent an up-to-date method of process optimalization, where other solutions have failed or haven’t given any satisfactory results. One of these processes is automatic placement of map symbols in such a way so that no symbols should mutually overlay. A genetic algorithm solving this task including an exact formulation and a definition of the initial conditions has been described in this paper. The algorithm efficiency will be tested in diploma works in Institute of Geodesy, Faculty of Civil Engineering, Brno University of Technology.
13
Zastosowanie obliczeń ewolucyjnych w zagadnieniach związanych z analizą sieci hydraulicznych
63%
Handzel Z. , Gajer M. , Jamróz D.
Elektronika : konstrukcje, technologie, zastosowania
|
2015
|
tom Vol. 56, nr 1
56-58
PL
W artykule zaproponowano wykorzystanie algorytmów ewolucyjnych w celu przeprowadzania analizy oczkowych sieci hydraulicznych. Zadaniem algorytmu ewolucyjnego jest wyznaczenie wartości przepływów w poszczególnych gałęziach arbitralnie zadanej sieci hydraulicznej. W artykule zaproponowano sposób kodowania rozwiązań na materiale genetycznym ewoluujących osobników oraz zdefiniowano postać funkcji dopasowania pozwalającej na ocenę rozwiązań odnajdowanych w toku procesów ewolucyjnych.
EN
In the paper we propose to use evolutionary algorithms for the purpose of analysis of hydraulic networks. The aim of evolutionary algorithm is to determine the values of flow in the branches of arbitrarily given hydraulic network. In the paper we propose the way of coding of solutions on genetic material of evolving individuals and we define the fitness function to evaluate solutions found during the process of evolution.
14
A genetic algorithm how to solve a puzzle and its using in cartography
63%
Bartonek D.
Acta Scientiarum Polonorum. Geodesia et Descriptio Terrarum
|
2005
|
tom 04
|
nr 2
15
Content available remote Systemowy algorytm ewolucyjny (SAE)
63%
Tchórzewski J. R.
Bio-Algorithms and Med-Systems
|
2005
|
tom Vol. 1, no. 1/2
61--64
PL
Praca zawiera propozycję nowej metody z grupy algorytmów genetycznych i ewolucyjnych nazwanej systemowym algorytmem ewolucyjnym (SAE). Klasyczne już algorytmy genetyczne i ewolucyjne nie zawierają na przykład metody prowadzącej do otrzymywania pierwotnej populacji wprost z systemu oraz adekwatnego sposobu na otrzymywanie nowej populacji (odpowiednio zdefiniowanej funkcji przystosowania). Artykuł zawiera ponadto szereg definicji takich jak: strukturalne i parametryczne zmiany, kod informacyjny rozwoju systemu, rozbieżności systemowe pomiędzy systemem a otoczeniem (uogólnienie pojęcia funkcji przystosowania), mapy wiedzy o rozwoju systemu itp.
EN
This paper contains proposition of new method of evolving algorithm called evolving algorithm of system (SAE). Classical algorithms are not, for example, furnished with a method of getting population directly from systems and adequacy methods to qualify artificial genetic code to new populations. The article presents the way to produce genetic code directly from systems and also defines steps leading to new population. Besides this, the article presents definitions of structural and parametric changes, information code of systems, divergence between system and environment (special fitness function), knowledge maps on system development, and others.
16
Content available A genatic algorithm how to solve a puzzle and its using in cartography
44%
Bartoněk D.
Acta Scientiarum Polonorum. Geodesia et Descriptio Terrarum
|
2005
|
tom Vol. 4, nr 2
15-23
EN
Genetic algorithms represent an up-to-date method of process optimization, where other solutions have failed or haven't given any satisfactory results. One of these processes is puzzle solving, where fragments have to be placed into the defined shape in such a way so that no fragment should mutually overlay and the whole shape area will be filled with all of these fragments. A genetic algorithm solving this task including an exact formulation and a definition of the initial conditions based on cluster analysis has been described in this paper. The algorithm efficiency will be tested in diploma works in Institute of Geodesy, Faculty of Civil Engineering, University of Technology, Brno. The results will be used in the application for cartograms creation.
PL
Algorytmy genetyczne reprezentują nowoczesne metody optymalizacji procesów, dla których inne rozwiązania zawiodły lub nie dały satysfakcjonujących rezultatów. Jednym z takich procesów jest rozwiązywanie układanek - puzli, w których fragmenty muszą być wstawione w zdefiniowany kształt w ten sposób, aby żadne się nawzajem nie nakładały, a kształt zawierał wszystkie zadane fragmenty. Praca niniejsza zawiera opis algorytmu genetycznego rozwiązującego takie zadanie wraz ze ścisłą formułą rozwiązania oraz definicją warunków początkowych, bazującą na analizie skupień. Skuteczność algorytmu będzie testowana w pracy dyplomowej w Instytucie Geodezji na Wydziale Budownictwa, Politechniki w Brnie. Rezultaty zostaną wykorzystane przy tworzeniu kartogramów.
17
Optimization methods based on genetic algorithm
38%
Klieštik T. , Kráľ P.
Logistyka
|
2009
|
tom nr 6
CD-CD
EN
This article dealt with genetic algorithm. Genetic algorithms belong to one of the stochastic optimizing methods inspired by nature. We can use them in all the situations where search for the exact solution of everyday tasks with the help of systematic examination is infinite. This is why they enable elegant way of solving complex problems.
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