Temat: differential evolution

Skocz do pozycji: 1.

Tytuł:: Adapting differential evolution algorithms for continuous optimization via greedy adjustment of control parameters
Autorzy:: Leon, M.
Xiong, N.
Tematy:: differential evolution
optimization
parameter adaptation; Pokaż więcej
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:: https://bibliotekanauki.pl/articles/91824.pdf Link otwiera się w nowym oknie
Opis:: Differential evolution (DE) presents a class of evolutionary and meta-heuristic techniques that have been applied successfully to solve many real-world problems. However, the performance of DE is significantly influenced by its control parameters such as scaling factor and crossover probability. This paper proposes a new adaptive DE algorithm by greedy adjustment of the control parameters during the running of DE. The basic idea is to perform greedy search for better parameter assignments in successive learning periods in the whole evolutionary process. Within each learning period, the current parameter assignment and its neighboring assignments are tested (used) in a number of times to acquire a reliable assessment of their suitability in the stochastic environment with DE operations. Subsequently the current assignment is updated with the best candidate identified from the neighborhood and the search then moves on to the next learning period. This greedy parameter adjustment method has been incorporated into basic DE, leading to a new DE algorithm termed as Greedy Adaptive Differential Evolution (GADE). GADE has been tested on 25 benchmark functions in comparison with five other DE variants. The results of evaluation demonstrate that GADE is strongly competitive: it obtained the best rank among the counterparts in terms of the summation of relative errors across the benchmark functions with a high dimensionality.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: The grouping differential evolution algorithm for multi-dimensional optimization problems
Autorzy:: Piotrowski, A. P.
Napiórkowski, J. J.
Tematy:: differential evolution
multidimensional problems
multimodal problems
metaheuristics; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Powiązania:: https://bibliotekanauki.pl/articles/969839.pdf Link otwiera się w nowym oknie
Opis:: A variant of the Differential Evolution method is presented. The classical Differential Evolution approach is very successful for simple problems, but does not perform well enough for troublesome multi-dimensional non-convex continuous functions. To overcome some of the drawbacks, the Grouped Multi-Strategy Differential Evolution algorithm is proposed here. The main idea behind the new approach is to exploit the knowledge about the local minima already found in different parts of the search space in order to facilitate further search for the global one. In the proposed method, the population is split into four groups: three of them rarely communicate with the others, but one is allowed to gain all available knowledge from the whole population throughout the search process. The individuals simultaneously use three different crossover/mutation strategies, which makes the algorithm more flexible. The proposed approach was compared with two Differential Evolution based algorithms on a set of 10- to 100-dimensional test functions of varying difficulty. The proposed method achieved very encouraging results; its advantage was especially significant when more difficult 50- and 100-dimensional problems were considered. When dividing population into separate groups, the total number of individuals becomes a crucial restriction. Hence, the impact of the number of individuals on the performance of the algorithms was studied. It was shown that increasing the number of individuals above the number initially proposed for classic Differential Evolution method is in most cases not advantageous and sometimes may even result in deterioration of results.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Optimization the dynamical parameters of three phase induction motor using genetic algorithm
Autorzy:: Mohammed, M.H.
Tematy:: induction motor
genetic algorithm
differential evolution
DE; Pokaż więcej
Wydawca:: Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Powiązania:: https://bibliotekanauki.pl/articles/376222.pdf Link otwiera się w nowym oknie
Opis:: This paper deals with the optimization of the induction motor design with respect to torque as a dynamical parameter. Most studies on the design of an induction motor using optimization techniques are concerned with the minimization of the motor cost and describe the optimization technique that was employed, giving the results of a single (or several) optimal design(s).Procedure includes the relationship between torque of motor and other effects as they occur in an optimal design. The optimization method that was used in this paper is Differential Evolution as genetic algorithm. Optimal results are in picture as curves or in tabula.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Effect of strategy adaptation on differential evolution in presence and absence of parameter adaptation: an investigation
Autorzy:: Dawar, D.
Ludwig, S. A.
Tematy:: evolutionary algorithms
differential evolution
mutation strategy
adaptive control; Pokaż więcej
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:: https://bibliotekanauki.pl/articles/91882.pdf Link otwiera się w nowym oknie
Opis:: Differential Evolution (DE) is a simple, yet highly competitive real parameter optimizer in the family of evolutionary algorithms. A significant contribution of its robust performance is attributed to its control parameters, and mutation strategy employed, proper settings of which, generally lead to good solutions. Finding the best parameters for a given problem through the trial and error method is time consuming, and sometimes impractical. This calls for the development of adaptive parameter control mechanisms. In this work, we investigate the impact and efficacy of adapting mutation strategies with or without adapting the control parameters, and report the plausibility of this scheme. Backed with empirical evidence from this and previous works, we first build a case for strategy adaptation in the presence as well as in the absence of parameter adaptation. Afterwards, we propose a new mutation strategy, and an adaptive variant SA-SHADE which is based on a recently proposed self-adaptive memory based variant of Differential evolution, SHADE. We report the performance of SA-SHADE on 28 benchmark functions of varying complexity, and compare it with the classic DE algorithm (DE/Rand/1/bin), and other state-of-the-art adaptive DE variants including CoDE, EPSDE, JADE, and SHADE itself. Our results show that adaptation of mutation strategy improves the performance of DE in both presence, and absence of control parameter adaptation, and should thus be employed frequently.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Differential evolution with competitive setting of control parameters
Autorzy:: Tvrdik, J.
Tematy:: global optimization
differential evolution
self-adaptation
numerical comparison; Pokaż więcej
Wydawca:: Politechnika Gdańska
Powiązania:: https://bibliotekanauki.pl/articles/1943260.pdf Link otwiera się w nowym oknie
Opis:: This paper is focused on the adaptation of control parameters in differential evolution. Competition of various control parameter settings was proposed in order to ensure self-adaptation of parameter values in the search process. Several variants of such algorithm were tested on six functions at four levels of the search-space dimension. The competitive variants of differential evolution have proved to be more reliable and less time-consuming than the standard differential evolution. The competitive variants have also outperformed other tested algorithms in their reliability and convergence rate.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Intelligent hybrid fuzzy logic system for damage detection of beam-like structural elements
Autorzy:: Sahu, S.
Kumar, P. B.
Parhi, D. R.
Tematy:: fuzzy logic
differential evolution algorithm
crack
natural frequency; Pokaż więcej
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Powiązania:: https://bibliotekanauki.pl/articles/281457.pdf Link otwiera się w nowym oknie
Opis:: Fuzzy logic has been used in different research fields for more than three decades. It has become a robust method to solve complex and intricate problems which are otherwise difficult to solve by traditional methods. But it still requires some human experience and knowledge. In the present study, an attempt is made to design a hybrid optimization technique for automatic formation of the fuzzy knowledge based rules using an evolutionary algorithm. This hybridization technique has been applied in the field of damage detection and location of cracks in cracked structural elements. In this paper, a robust fault diagnostic tool based on a differential evolution algorithm and fuzzy logic has been proposed. Theoretical and Finite Element analyzes are done to model the crack and to find the effect of the presence of cracks on changes of vibrational characteristic (natural frequencies) of a fixed-fixed beam. The inputs to DEA-FL system are the first three relative natural frequencies, and the outputs from the system are the relative crack depth and relative crack location. For the validation of the results obtained from the proposed method and to check the robustness of the controller, experimental analysis is performed. To find average error rates, the bootstrap method has been adopted.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Shape Optimization of Mufflers Composed of Multiple Rectangular Fin-Shaped Chambers Using Differential Evolution Method
Autorzy:: Chiu, M.-C.
Chang, Y.-C.
Cheng, H.-C.
Tai, W.-T.
Tematy:: fin
multi-chamber
high-order-mode
differential evolution; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/177237.pdf Link otwiera się w nowym oknie
Opis:: There has been considerable research done on multi-chamber mufflers used in the elimination of industrial venting noise. However, most research has been restricted to lower frequencies using the plane wave theory. This has led to underestimating acoustical performances at higher frequencies. Additionally, because of the space-constrained problem in most plants, the need for optimization of a compact muffler seems obvious. Therefore, a muffler composed of multiple rectangular fin-shaped chambers is proposed. Based on the eigenfunction theory, a four-pole matrix used to evaluate the acoustic performance of mufflers will be deduced. A numerical case for eliminating pure tones using a three-fin-chamber muffler will also be examined. To delineate the best acoustical performance of a space-constrained muffler, a numerical assessment using the Differential Evolution (DE) method is adopted. Before the DE operation for pure tone elimination can be carried out, the accuracy of the mathematical model must be checked using experimental data. The results reveal that the broadband noise has been efficiently reduced using the three-fin-chamber muffler. Consequently, a successful approach in eliminating a pure tone using optimally shaped three-fin-chamber mufflers and a differential evolution method within a constrained space has been demonstrated.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: A new multi-objective optimization algorithm based on differential evolution and neighborhood exploring evolution strategy
Autorzy:: Lobato, F. S.
Steffen, Jr, V.
Tematy:: multi-objective optimization
differential evolution
neighborhood exploring
evolution strategy
sorting strategy; Pokaż więcej
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:: https://bibliotekanauki.pl/articles/91590.pdf Link otwiera się w nowym oknie
Opis:: In this paper a new optimization algorithm based on Differential Evolution, non-dominated sorting strategy and neighborhood exploration strategy for guaranteeing convergence and diversity through the generation of neighborhoods of different sizes to potential candidates in the population is presented. The performance of the algorithm proposed is validated by using standard test functions and metrics commonly adopted in the specialized literature. The sensitivity analysis of some relevant parameters of the algorithm is performed and compared with the classical DE algorithm without the strategy of neighborhood exploration and with other state-of-the-art evolutionary algorithms.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Solving the sudoku with the differential evolution
Ewolucja różnicowa w rozwiązywaniu Sudoku
Autorzy:: Boryczka, U.
Juszczuk, P.
Tematy:: ewolucja różnicowa
sudoku
optymalizacja dyskretna
differential evolution
discrete optimization; Pokaż więcej
Wydawca:: Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Powiązania:: https://bibliotekanauki.pl/articles/341123.pdf Link otwiera się w nowym oknie
Opis:: In this paper, we present the application of the Differential Evolution (DE) algorithm to solving the combinatorial problem. The advantage of the DE algorithm is its capability of avoiding so-called "local minima" within the considered search space. Thanks to the special operator of the adaptive mutation, it is possible to direct the searching process within the solution space. The DE algorithm applies the selection operator that selects from the child population only the offspring with the greater value of the fitness function in comparison to their parents. An algorithm applied to a combinatorial optimization problem: Sudoku puzzle is presented. Sudoku consists of a nine by nine grid, divided into nine three by three boxes. Each of the eighty-one squares should be filled in with a number between one and nine. In this article we show, that the mutation schema has significant impact on the quality of created solution.
W artykule przedstawimy propozycję zastosowania algorytmu ewolucji różnicowej do rozwiązywania problemów kombinatorycznych. Przewagą ewolucji różnicowej jest zdolność do unikania optimów lokalnych w przestrzeni przeszukiwań. Specjalny operator mutacji pozwala ukierunkować proces poszukiwań rozwiązania. W ewolucji różnicowej stosowany jest operator selekcji, który promuje tylko najlepiej przystosowane osobniki z populacji rodziców i potomków. Przedstawimy zastosowanie opisanego algorytmu do problemu rozwiązywania Sudoku. Sudoku składa się z planszy 9 na 9, podzielonej na 9 sekcji -każda o rozmiarze 3 na 3 elementy. Każda z 81 kratek powinna zostać wypełniona wartością z przedziału 1 do 9. W artykule pokażemy, że ewolucja różnicowa pozwala na rozwiązywanie Sudoku.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Self-Adaptive Differential Evolution with Hybrid Rules of Perturbation for Dynamic Optimization
Autorzy:: Trojanowski, K.
Raciborski, M.
Kaczyński, P.
Tematy:: adaptive differential evolution
dynamic optimization
symmetric a-stable distribution; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/308439.pdf Link otwiera się w nowym oknie
Opis:: In this paper an adaptive differential evolution approach for dynamic optimization problems is studied. A new benchmark suite Syringa is also presented. The suite allows to generate test-cases from a multiple number of dynamic optimization classes. Two dynamic benchmarks: Generalized Dynamic Benchmark Generator (GDBG) and Moving Peaks Benchmark (MPB) have been simulated in Syringa and in the presented research they were subject of the experimental research. Two versions of adaptive differential evolution approach, namely the jDE algorithm have been heavily tested: the pure version of jDE and jDE equipped with solutions mutated with a new operator. The operator uses a symmetric ?-stable distribution variate for modification of the solution coordinates.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Solution of linear and non-linear boundary value problems using population-distributed parallel differential evolution
Autorzy:: Nasim, Amnah
Burattini, Laura
Fateh, Muhammad Faisal
Zameer, Aneela
Tematy:: parallel evolutionary algorithms
differential evolution
boundary value problems
optimization; Pokaż więcej
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:: https://bibliotekanauki.pl/articles/91569.pdf Link otwiera się w nowym oknie
Opis:: Cases where the derivative of a boundary value problem does not exist or is constantly changing, traditional derivative can easily get stuck in the local optima or does not factually represent a constantly changing solution. Hence the need for evolutionary algorithms becomes evident. However, evolutionary algorithms are compute-intensive since they scan the entire solution space for an optimal solution. Larger populations and smaller step sizes allow for improved quality solution but results in an increase in the complexity of the optimization process. In this research a population-distributed implementation for differential evolution algorithm is presented for solving systems of 2nd-order, 2-point boundary value problems (BVPs). In this technique, the system is formulated as an optimization problem by the direct minimization of the overall individual residual error subject to the given constraint boundary conditions and is then solved using differential evolution in the sense that each of the derivatives is replaced by an appropriate difference quotient approximation. Four benchmark BVPs are solved using the proposed parallel framework for differential evolution to observe the speedup in the execution time. Meanwhile, the statistical analysis is provided to discover the effect of parametric changes such as an increase in population individuals and nodes representing features on the quality and behavior of the solutions found by differential evolution. The numerical results demonstrate that the algorithm is quite accurate and efficient for solving 2nd-order, 2-point BVPs.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: Control Strategy of Parallel Systems with Efficiency Optimisation in Switched Reluctance Generators
Autorzy:: Zan, Xiaoshu
Lin, Hang
Xu, Guanqun
Zhao, Tiejun
Gong, Yi
Tematy:: switched reluctance generator
parallel system
efficiency optimization
differential evolution algorithm; Pokaż więcej
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:: https://bibliotekanauki.pl/articles/1956008.pdf Link otwiera się w nowym oknie
Opis:: To solve motor heating and life shortening of parallel switched reluctance generator (SRG) induced by uneven output currents due to different external characteristics, we generally adopt current sharing control (CSC) to make each parallel generator undertake large load currents on average to improve the reliability of parallel power generation system. However, the method usually causes additional loss of power because it does not consider the efficiency characteristics of each parallel generator. Therefore, with the efficiency expression for the parallel system of SRG established and analysed, the control strategy based on differential evolution (DE) algorithm is proposed as a mechanism by which to enhance generating capacity and reliability of multi-machine power generation from the perspective of efficiency optimisation. We re-adjust the reference current of each parallel generator to transform the working point of each generator and implement the efficiency optimisation of parallel system. The performance of the proposed control method is evaluated in detail by the simulation and experiment, and comparison with traditional CSC is carried out as well.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: Design of Low Power Thinned Smart Antenna for 6G Sky Connection
Autorzy:: Khan, Anindita
Roy, Jibendu Sekhar
Tematy:: differential evolution
power saving
signal processing algorithms
smart antenna
thinned arra; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/58906680.pdf Link otwiera się w nowym oknie
Opis:: To improve radio access capability, sky connectionsrelying on satellites or unmanned aerial vehicles (UAV), as wellas high-altitude platforms (HAP) will be exploited in6G wirelesscommunication systems, complementing terrestrial networks.For long-distance communication, a large smart antenna will beused that is characterized by high amounts of power consumedby digital beamformers. This paper focuses on reducing powerconsumption by relying on a thinned smart antenna (TSA). Theperformance of TSA is investigated in the sub-6GHz band. Thedifferential evolution (DE) algorithm is used to optimize excita-tion weights of the individual dipoles in the antenna array andthese excitation weights are then used in TSA for beamforming,with signal processing algorithms deployed. The DE techniqueis used with the least mean square, recursive least square andsample matrix inversion algorithms. The proposed method of-fers almost the same directivity, simultaneously ensuring lowerside lobes (SLL) and reduced power consumption. For a TSAof20,31, and64dipoles, the power savings are20%,19.4%,and17.2%, respectively. SLL reductions achieved, in turn, varyfrom 5.2 dB to 8.1 dB.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: Novel optimization method for mobile magnetostatic shield and test applications
Autorzy:: Ralf, Patrick Alexander
Kreischer, Christian
Tematy:: differential evolution
evolutionary algorithm
magnetostatic passive shielding
mobile application
optimization
spherical shells; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2135737.pdf Link otwiera się w nowym oknie
Opis:: This article provides an optimized solution to the problem of passive shielding against static magnetic fields with any number of spherical shells. It is known, that the shielding factor of a layered structure increases in contrast to a single shell with the same overall thickness. For the reduction of weight and cost by given material parameters and available space the best system for the layer positions has to be found. Because classic magnetically shielded rooms are very heavy, this system will be used to develop a transportable Zero-Gauss-Chamber. To handle this problem, a new way was developed, in which for the first time the solution with regard to shielding and weight was optimized. Therefore, a solution for the most general case of spherical shells was chosen with an adapted boundary condition. This solution was expanded to an arbitrary number of layers and permeabilities. With this analytic solution a differential evolution algorithm is able to find the best partition of the shells. These optimized solutions are verified by numerical solutions made by the Finite Element Method (FEM). After that the solutions of different raw data are determined and investigated.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: Learning finite Gaussian mixtures using differential evolution
Uczenie skończonych mieszanin rozkładów normalnych przy pomocy algorytmu ewolucji różnicowej
Autorzy:: Kwedlo, W.
Tematy:: mieszaniny rozkładów normalnych
ewolucja różnicowa
algorytm EM
Gaussian mixtures
differential evolution
EM algorithm; Pokaż więcej
Wydawca:: Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Powiązania:: https://bibliotekanauki.pl/articles/341041.pdf Link otwiera się w nowym oknie
Opis:: In the paper the problem of parameter estimation of finite mixture of multivariate Gaussian distributions is considered. A new approach based on differential evolution (DE) algorithm is proposed. In order to avoid problems with infeasibility of chromosomes our version of DE uses a novel representation, in which covariance matrices are encoded using their Cholesky decomposition. Numerical experiments involved three version of DE differing by the method of selection of strategy parameters. The results of experiments, performed on two synthetic and one real dataset indicate, that our method is able to correctly identify the parameters of the mixture model. The method is also able to obtain better solutions than the classical EM algorithm. Keywords: Gaussian mixtures, differential evolution, EM algorithm.
W artykule rozważono problem uczenia parametrów skończonej mieszaniny wielowymiarowych rozkładów normalnych. Zaproponowano nową metodę uczenia opartą na algorytmie ewolucji różnicowej. W celu uniknięcia problemów z niedopuszczalnością chromosomów algorytm ewolucji różnicowej wykorzystuje nową reprezentację, w której macierze kowariancji są reprezentowane przy pomocy dekompozycji Cholesky’ego. W eksperymentach wykorzystano trzy wersje algorytmu ewolucji różnicowej różniące się metodą˛ doboru parametrów. Wyniki eksperymentów, przeprowadzonych na dwóch syntetycznych i jednym rzeczywistym zbiorze danych, wskazują że zaproponowana metoda jest w stanie poprawnie identyfikować parametry modelu. Metoda ta osiąga również lepsze wyniki niż klasyczyny algorytm EM.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 16.

Tytuł:: Multi-AUV distributed task allocation based on the differential evolution quantum bee colony optimization algorithm
Autorzy:: Li, J.
Zhang, R.
Tematy:: differential evolution quantum artificial bee colony algorithm
multi-AUV
contract net
task allocation; Pokaż więcej
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Powiązania:: https://bibliotekanauki.pl/articles/259994.pdf Link otwiera się w nowym oknie
Opis:: The multi-autonomous underwater vehicle (AUV) distributed task allocation model of a contract net, which introduces an equilibrium coefficient, has been established to solve the multi-AUV distributed task allocation problem. A differential evolution quantum artificial bee colony (DEQABC) optimization algorithm is proposed to solve the multi-AUV optimal task allocation scheme. The algorithm is based on the quantum artificial bee colony algorithm, and it takes advantage of the characteristics of the differential evolution algorithm. This algorithm can remember the individual optimal solution in the population evolution and internal information sharing in groups and obtain the optimal solution through competition and cooperation among individuals in a population. Finally, a simulation experiment was performed to evaluate the distributed task allocation performance of the differential evolution quantum bee colony optimization algorithm. The simulation results demonstrate that the DEQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The DEQABC algorithm can effectively improve AUV distributed multi-tasking performance.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 17.

Tytuł:: Optimum design of fiber angle and hole orientation of an orthotropic plate
Autorzy:: Zhang, X.
Lu, A.
Wang, S.
Zhang, N.
Tematy:: orthotropic plate
fiber orientation angle
hole orientation angle
conformal transformation method
differential evolution algorithm; Pokaż więcej
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Powiązania:: https://bibliotekanauki.pl/articles/280011.pdf Link otwiera się w nowym oknie
Opis:: With the goal of decreasing the stress concentration along the hole boundary in an orthotropic plate under inequi-biaxial loadings, an optimum design of the fiber angle and hole orientation is presented. The maximum absolute tangential stress along the hole boundary is taken as the objective function, and the fiber orientation angle and the hole orientation angle are considered as design variables. The conformal transformation method of a complex function and the Differential Evolution (DE) algorithm are used. Two non-circular shapes, ellipse and hexagon are taken as examples to analyze the problem. Based on the results, we can conclude that the major axis of elliptical holes should be designed in the direction of the maximum external loading for a perforated structure in an orthotropic plate. However, the principal direction that has the larger Young’s modulus should be inclined to the direction of the minimum loading, especially for a significantly orthotropic plate.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 18.

Tytuł:: Solution of singular optimal control problems using the improved differential evolution algorithm
Autorzy:: Lobato, F. S.
Steffen, Jr, V.
Silva Neto, A. J.
Tematy:: differential evolution algorithm
optimal control
dynamic updating
population
convergence rate
mechanical engineering
chemical engineering; Pokaż więcej
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:: https://bibliotekanauki.pl/articles/91654.pdf Link otwiera się w nowym oknie
Opis:: The Differential Evolution algorithm, like other evolutionary techniques, presents as main disadvantage the high number of objective function evaluations as compared with classical methods. To overcome this disadvantage, this work proposes a new strategy for the dynamic updating of the population size to reduce the number of objective function evaluations. This strategy is based on the definition of convergence rate to evaluate the homogeneity of the population in the evolutionary process. The methodology is applied to the solution of singular optimal control problems in chemical and mechanical engineering. The results demonstrated that the methodology proposed represents a promising alternative as compared with other competing strategies.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 19.

Tytuł:: Deterministically guided differential evolution for constrained power dispatch with prohibited operating zones
Autorzy:: Jasper, J.
Victoire, T. A. A.
Tematy:: economic load dispatch
differential evolution
variable neighborhood search
prohibited operating zones
valve point effect; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/950670.pdf Link otwiera się w nowym oknie
Opis:: Department of Electrical Engineering, Anna University Regional Centre, Coimbatore, India This paper presents a new approach to solve economic load dispatch (ELD) problem in thermal units with non-convex cost functions using differential evolution technique (DE). In practical ELD problem, the fuel cost function is highly non linear due to inclusion of real time constraints such as valve point loading, prohibited operating zones and network transmission losses. This makes the traditional methods fail in finding the optimum solution. The DE algorithm is an evolutionary algorithm with less stochastic approach to problem solving than classical evolutionary algorithms.DE have the potential of simple in structure, fast convergence property and quality of solution. This paper presents a combination of DE and variable neighborhood search (VNS) to improve the quality of solution and convergence speed. Differential evolution (DE) is first introduced to find the locality of the solution, and then VNS is applied to tune the solution. To validate the DE-VNS method, it is applied to four test systems with non-smooth cost functions. The effectiveness of the DE-VNS over other techniques is shown in general.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Multiobjective optimiaztion of microstructure parameters in a thermoelastic porous material by means of differential evolution and elements of game theory
Autorzy:: Długosz, Adam
Schlieter, Tomasz
Tematy:: multiobjective optimization
thermoelasticity
porous materials
multiscale problem
representative volume element
differential evolution
game theory; Pokaż więcej
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Powiązania:: https://bibliotekanauki.pl/articles/29520065.pdf Link otwiera się w nowym oknie
Opis:: The paper is devoted to the optimization of the microstructure parameters of a porous medium under thermo-mechanical loading. Four different criteria related to the properties of the porous material have been proposed and numerically implemented. To solve a multiobjective problem, a novel method based on the coupling of differential evolution and elements of game theory is used. The proposed algorithm features an appropriate balance between exploration and exploitation of objective space, which is necessary for the successful optimization of these types of tasks with the use of numerical simulations. The model of the thermo-elastic porous material is composed of two-scale direct analysis based on a numerical homogenization. Direct thermoelastic analysis with representative volume element (RVE) and finite element method (FEM) is performed. Numerical example of the optimization illustrating the usefulness of the proposed method is included.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Training neural networks with a hybrid differential evolution algorithm
Uczenie sieci neuronowych hybrydowym algorytmem opartym na differential evolution
Autorzy:: Bandurski, K.
Kwedlo, W.
Tematy:: sieci neuronowe
differential evolution
gradienty sprzężone
minima lokalne
neural networks
conjugate gradients
local minima; Pokaż więcej
Wydawca:: Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Powiązania:: https://bibliotekanauki.pl/articles/341051.pdf Link otwiera się w nowym oknie
Opis:: A new hybrid method for feed forward neural network training, which combines differential evolution algorithm with a gradient-based approach is proposed. In the method, after each generation of differential evolution, a number of iterations of the conjugate gradient optimization algorithm is applied to each new solution created by the mutation and crossover operators. The experimental results show, that in comparison to the standard differential evolution the hybrid algorithm converges faster. Although this convergence is slower than that of classical gradient based methods, the hybrid algorithm has significantly better capability of avoiding local optima.
W artykule przedstawiono nową, hybrydową metodę uczenia sieci neuronowych, łączącą w sobie algorytm Differential Evolution z podejściem gradientowym. W nowej metodzie po każdej generacji algorytmu Differential Evolution, każde nowe rozwiązanie, powstałe w wyniu działania operatorów krzyżowania i mutacji, poddawane jest kilku iteracjom algorytmu optymalizacji wykorzystującego metodę gradientów sprzężonych.Wyniki eksperymentów wskazują, że nowy, hybrydowy algorytm ma szybszą zbieżność niż standardowy algorytm Differential Evolution. Mimo, iż zbieżność ta jest wolniejsza, niż w przypadku klasycznych metod gradientowych, algorytm hybrydowy potrafi znacznie lepiej unikać minimów lokalnych.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 22.

Tytuł:: A study on the synchronization behaviour of differential evolution and a self-adaptive extension
Autorzy:: Santucci, V.
Milani, A.
Vella, F.
Tematy:: synchronization
behaviour
differential evolution
DE
self-adaptive
extension
state of the art
adaptive DE; Pokaż więcej
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:: https://bibliotekanauki.pl/articles/91840.pdf Link otwiera się w nowym oknie
Opis:: Differential Evolution (DE) is a popular and efficient continuous optimization technique based on the principles of Darwinian evolution. Asynchronous Differential Evolution is a DE generalization that allows to regulate the synchronization mechanism of the algorithm by tuning two additional parameters. This paper, after providing a further experimental analysis of the impact of the DE synchronization scheme on the evolution, introduces three self-adaptive techniques to handle the synchronization parameters. Moreover the integration of these new regulatory synchronization techniques into state-of-the-art (self) adaptive DE schemes are also proposed. Experiments on widely accepted benchmark problems show that the new schemes are able to improve performances of the state-of-theart (self) adaptive DEs by introducing the new synchronization parameters in the online automated tuning process.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: The training of multiplicative neuron model based artificial neural networks with differential evolution algorithm for forecasting
Autorzy:: Bas, E.
Tematy:: artificial neural networks
multiplicative neuron model
differential evolution
algorithm
forecasting
sztuczne sieci neuronowe
algorytm
prognozowanie; Pokaż więcej
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:: https://bibliotekanauki.pl/articles/91575.pdf Link otwiera się w nowym oknie
Opis:: In recent years, artificial neural networks have been commonly used for time series forecasting by researchers from various fields. There are some types of artificial neural networks and feed forward artificial neural networks model is one of them. Although feed forward artificial neural networks gives successful forecasting results they have a basic problem. This problem is architecture selection problem. In order to eliminate this problem, Yadav et al. (2007) proposed multiplicative neuron model artificial neural network. In this study, differential evolution algorithm is proposed for the training of multiplicative neuron model for forecasting. The proposed method is applied to two well-known different real world time series data.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation
Autorzy:: Pandiarajan, K.
Babulal, C. K.
Tematy:: non-dominated sorting genetic algorithm
generation rescheduling
particle swarm optimization (PSO)
differential evolution
overload index; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/141059.pdf Link otwiera się w nowym oknie
Opis:: This paper presents an effective method of network overload management in power systems. The three competing objectives 1) generation cost 2) transmission line overload and 3) real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO) and Differential evolution (DE). Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices
Autorzy:: Bhattacharyya, B.
Gupta, V. K.
Kumar, S.
Tematy:: FACTS devices
line power flow
FACTS devices & its optimal locations
genetic algorithm
differential evolution technique; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/141459.pdf Link otwiera się w nowym oknie
Opis:: The problem of improving the voltage profile and reducing power loss in electrical networks must be solved in an optimal manner. This paper deals with comparative study of Genetic Algorithm (GA) and Differential Evolution (DE) based algorithm for the optimal allocation of multiple FACTS (Flexible AC Transmission System) devices in an interconnected power system for the economic operation as well as to enhance loadability of lines. Proper placement of FACTS devices like Static VAr Compensator (SVC), Thyristor Controlled Switched Capacitor (TCSC) and controlling reactive generations of the generators and transformer tap settings simultaneously improves the system performance greatly using the proposed approach. These GA & DE based methods are applied on standard IEEE 30 bus system. The system is reactively loaded starting from base to 200% of base load. FACTS devices are installed in the different locations of the power system and system performance is observed with and without FACTS devices. First, the locations, where the FACTS devices to be placed is determined by calculating active and reactive power flows in the lines. GA and DE based algorithm is then applied to find the amount of magnitudes of the FACTS devices. Finally the comparison between these two techniques for the placement of FACTS devices are presented.
Dostawca treści:: Biblioteka Nauki

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