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Tytuł:
Single-objective optimal power flow for electric power systems based on crow search algorithm
Autorzy:
Fathy, A.
Abdelaziz, A.
Powiązania:
https://bibliotekanauki.pl/articles/140618.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
crow search algorithm
distribution network
optimal power flow
Opis:
This paper presents the application of a recent meta-heuristic optimization technique named a crow search algorithm (CSA) in solving the problem of an optimal power flow (OPF) for electric power systems. Various constrained objective functions, total fuel cost, active power loss and pollutant emission are proposed. The generators’ output powers, generators’ terminal voltages, transmission lines’ taps and the shunt capacitors’ reactive powers are considered as variables to be designed. The proposed methodology based on the CSA is applied on an IEEE 30-bus system and IEEE 118-bus system. The obtained results via the CSA are compared to others and they ensure the superiority of the CSA in solving the OPF problem in electric power systems.
Źródło:
Archives of Electrical Engineering; 2018, 67, 1; 123-138
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cryptographically Strong Elliptic Curves of Prime Order
Autorzy:
Barański, Marcin
Gliwa, Rafał
Szmidt, Janusz
Powiązania:
https://bibliotekanauki.pl/articles/1844627.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Mersenne primes
elliptic curves
security requirements
search algorithm
Magma
Opis:
The purpose of this paper is to generate cryptographically strong elliptic curves over prime fields Fp, where p is a Mersenne prime, one of the special primes or a random prime. We search for elliptic curves which orders are also prime numbers. The cryptographically strong elliptic curves are those for which the discrete logarithm problem is computationally hard. The required mathematical conditions are formulated in terms of parameters characterizing the elliptic curves. We present an algorithm to generate such curves. Examples of elliptic curves of prime order are generated with Magma.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 2; 207-212
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fault Current Limiter optimal sizing considering different Microgrid operational modes using Bat and Cuckoo Search Algorithm
Autorzy:
Arani, A. A. K.
Bayati, N.
Mohammadi, R.
Gharehpetian, G. B.
Sadeghi, S. H.
Powiązania:
https://bibliotekanauki.pl/articles/140644.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fault current limiter (FCL)
Bat Algorithm (BA)
Cuckoo Search Algorithm (CSA)
microgrid (MG)
Opis:
Nowadays, the development of smart grids has been the focus of attention due to its advantages for power systems. One of the aspects of smart grids defined by using distributed generation (DG) in a low voltage network is a microgrid (MG). Based on its operational states, MG can operate in different configurations such as grid-connected mode or off-grid mode. The switching between these states is one of the challenging issues in this technical area. The fault currents in different buses have higher value compared to islanded mode of MG when the MG is connected to the main grid, which influences the protection equipment. In this situation, some electrical devices may be damaged due to the fault currents. Application of a fault current limiter (FCL) is considered as an effective way to overcome this challenge. The optimal size of these FCLs can optimize the performance of an MG. In this paper, an index for FCL size optimization has been used. In addition, two optimization algorithms (Bat Algorithm and Cuckoo Search Algorithm) have been applied to the problem. The application of an FCL has been studied in grid-connected and islanded-mode. In addition, the application of the capacitor bank in both modes has been investigated. The results of simulations carried out by MATLAB have been presented and compared.
Źródło:
Archives of Electrical Engineering; 2018, 67, 2; 321--332
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition
Autorzy:
Bentata, Khadidja
Mohammedi, Ahmed
Benslimane, Tarak
Powiązania:
https://bibliotekanauki.pl/articles/1845531.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
photovoltaic system
maximum power point tracking
partial shading
cuckoo search algorithm
Opis:
The solar photovoltaic output power fluctuates according to solar irradiation, temperature, and load impedance variations. Due to the operating point fluctuations, extracting maximum power from the PV generator, already having a low power conversion ratio, becomes very complicated. To reach a maximum power operating point, a maximum power point tracking technique (MPPT) should be used. Under partial shading condition, the nonlinear PV output power curve contains multiple maximum power points with only one global maximum power point (GMPP). Consequently, identifying this global maximum power point is a difficult task and one of the biggest challenges of partially shaded PV systems. The conventional MPPT techniques can easily be trapped in a local maximum instead of detecting the global one. The artificial neural network techniques used to track the GMPP have a major drawback of using huge amount of data covering all operating points of PV system, including different uniform and non-uniform irradiance cases, different temperatures and load impedances. The biological intelligence techniques used to track GMPP, such as grey wolf algorithm and cuckoo search algorithm (CSA), have two main drawbacks; to be trapped in a local MPP if they have not been well tuned and the precision-transient tracking time complex paradox. To deal with these drawbacks, a Distributive Cuckoo Search Algorithm (DCSA) is developed, in this paper, as GMPP tracking technique. Simulation results of the system for different partial shading patterns demonstrated the high precision and rapidity, besides the good reliability of the proposed DCSA- GMPPT technique, compared to the conventional CSA-GMPPT.
Źródło:
Archives of Control Sciences; 2021, 31, 3; 495-526
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition
Autorzy:
Bentata, Khadidja
Mohammedi, Ahmed
Benslimane, Tarak
Powiązania:
https://bibliotekanauki.pl/articles/1845518.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
photovoltaic system
maximum power point tracking
partial shading
cuckoo search algorithm
Opis:
The solar photovoltaic output power fluctuates according to solar irradiation, temperature, and load impedance variations. Due to the operating point fluctuations, extracting maximum power from the PV generator, already having a low power conversion ratio, becomes very complicated. To reach a maximum power operating point, a maximum power point tracking technique (MPPT) should be used. Under partial shading condition, the nonlinear PV output power curve contains multiple maximum power points with only one global maximum power point (GMPP). Consequently, identifying this global maximum power point is a difficult task and one of the biggest challenges of partially shaded PV systems. The conventional MPPT techniques can easily be trapped in a local maximum instead of detecting the global one. The artificial neural network techniques used to track the GMPP have a major drawback of using huge amount of data covering all operating points of PV system, including different uniform and non-uniform irradiance cases, different temperatures and load impedances. The biological intelligence techniques used to track GMPP, such as grey wolf algorithm and cuckoo search algorithm (CSA), have two main drawbacks; to be trapped in a local MPP if they have not been well tuned and the precision-transient tracking time complex paradox. To deal with these drawbacks, a Distributive Cuckoo Search Algorithm (DCSA) is developed, in this paper, as GMPP tracking technique. Simulation results of the system for different partial shading patterns demonstrated the high precision and rapidity, besides the good reliability of the proposed DCSA-GMPPT technique, compared to the conventional CSA-GMPPT.
Źródło:
Archives of Control Sciences; 2021, 31, 3; 495-526
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Balancing of a linear elastic rotor-bearing system with arbitrarily distributed unbalance using the Numerical Assembly Technique
Autorzy:
Quinz, Georg
Prem, Marcel S.
Klanner, Michael
Ellermann, Katrin
Powiązania:
https://bibliotekanauki.pl/articles/2086883.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Numerical Assembly Technique
rotor dynamics
modal balancing
recursive eigenvalue search algorithm
dynamika wirnika
wyważanie modalne
Opis:
In this paper, a new application of the Numerical Assembly Technique is presented for the balancing of linear elastic rotor-bearing systems with a stepped shaft and arbitrarily distributed mass unbalance. The method improves existing balancing techniques by combining the advantages of modal balancing with the fast calculation of an efficient numerical method. The rotating stepped circular shaft is modelled according to the Rayleigh beam theory. The Numerical Assembly Technique is used to calculate the steady-state harmonic response, eigenvalues and the associated mode shapes of the rotor. The displacements of a simulation are compared to measured displacements of the rotor-bearing system to calculate the generalized unbalance for each eigenvalue. The generalized unbalances are modified according to modal theory to calculate orthogonal correction masses. In this manner, a rotor-bearing system is balanced using a single measurement of the displacement at one position on the rotor for every critical speed. Three numerical examples are used to show the accuracy and the balancing success of the proposed method.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 6; e138237, 1--7
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Embedded direct search of optimal designs for finite noise experiments
Optymalne planowanie eksperymentów w przypadku dużego szumu metodą homotopii opartej na bezgradientowej minimalizacji
Autorzy:
Schulz, F.
Frischmuth, K.
Powiązania:
https://bibliotekanauki.pl/articles/224216.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
planowanie eksperymentu
układ dynamiczny
optymalizacja
model nieliniowy
parameter identification
nonlinear regression
embedding method
direct search algorithm
Opis:
We study experimental designs for the identification of nonlinear model parameters. As optimality criterion we assume minimality of the error in a huge number of identifications run on simulated data, which are generated with known parameters and a given error distribution. The optimal design depends on the nonlinear parameters. We find the optimal solution set by combining a path following strategy and a direct search method.
W pracy badane są optymalne plany eksperymentów wykonywanych do celów identyfikacji parametrów modelu nieliniowego układu dynamicznego. Jako kryterium optymalności przyjęto minimum błędów otrzymanych w dużej liczbie identyfikacji wykonanych na symulowanych danych, które zostały wygenerowane ze znanymi parametrami i przy założonym rozkładzie błędów. Optymalny plan zależy od parametrów modelu. Badano metody bezgradientowe połączone z homotopia, które okazują się bardzo efektywne w przypadku rozpatrywanego zagadnienia. Wyniki otrzymane w przypadku skończonych wartości błędów mogą się istotnie różnić od wyników otrzymanych z wykorzystaniem teorii asymptotycznej dla małego szumu.
Źródło:
Archives of Transport; 2010, 22, 1; 119-137
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid
Autorzy:
Khoshayand, Hossein Ali
Wattanapongsakorn, Naruemon
Mahdavian, Mehdi
Ganji, Ehsan
Powiązania:
https://bibliotekanauki.pl/articles/2202555.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
backward-forward load distribution
fuzzy logic
iterative search algorithm
multi-objective optimization
shortest distance from the origin
weighted sum
Opis:
One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.
Źródło:
Archives of Electrical Engineering; 2023, 72, 1; 253--271
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor
Autorzy:
Knypiński, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/2204509.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid cuckoo search algorithm
heuristic algorithms
multi-objective optimization
permanent magnet synchronous motor
PMSM
algorytm kukułki hybrydowy
algorytm Cuckoo
algorytm heurystyczny
optymalizacja wielocelowa
silnik synchroniczny z magnesem trwałym
Opis:
The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144586
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimal design of RC frames using a modified hybrid PSOGSA algorithm
Optymalny projekt ramy RC z wykorzystaniem zmodyfikowanego algorytmu hybrydowego PSOGSA
Autorzy:
Chutani, S.
Singh, J.
Powiązania:
https://bibliotekanauki.pl/articles/230376.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
projekt optymalny
konstrukcja żelbetowa
optymalizacja demokratyczna roju cząstek
samoadaptacyjny algorytm
grawitacyjnego wyszukiwania
projektowanie
Indie
norma indyjska
optimum design
reinforced concrete structure
democratic particle swarm optimization
selfadaptive gravitational search algorithm
design
Indian standard
Opis:
The present study has been taken up to emphasize the role of the hybridization process for optimizing a given reinforced concrete (RC) frame. Although various primary techniques have been hybrid in the past with varying degree of success, the effect of hybridization of enhanced versions of standard optimization techniques has found little attention. The focus of the current study is to see if it is possible to maintain and carry the positive effects of enhanced versions of two different techniques while using their hybrid algorithms. For this purpose, enhanced versions of standard particle swarm optimization (PSO) and a standard gravitational search algorithm (GSA), were considered for optimizing an RC frame. The enhanced version of PSO involves its democratization by considering all good and bad experiences of the particles, whereas the enhanced version of the GSA is made self-adaptive by considering a specific range for certain parameters, like the gravitational constant and a set of agents with the best fitness values. The optimization process, being iterative in nature, has been coded in C++. The analysis and design procedure is based on the specifications of Indian codes. Two distinct advantages of enhanced versions of standard PSO and GSA, namely, better capability to escape from local optima and a faster convergence rate, have been tested for the hybrid algorithm. The entire formulation for optimal cost design of a frame includes the cost of beams and columns. The variables of each element of structural frame have been considered as continuous and rounded off appropriately to consider practical limitations. An example has also been considered to emphasize the validity of this optimum design procedure.
W niniejszym artykule przedstawiono bardziej realistyczny i optymalny projekt żlbetowych ram konstrukcyjnych (RC) poprzez hybrydyzację ulepszonych wersji standardowej optymalizacji roju cząsteczek (PSO) oraz standardowy algorytm wyszukiwania grawitacyjnego (GSA). Podejście proponowane w niniejszej pracy koncentruje się na hybrydyzacji ulepszonych wersji standardowej optymalizacji roju cząsteczek (PSO) oraz standardowym algorytmie wyszukiwania grawitacyjnego (GSA). PSO została zdemokratyzowana poprzez uwzględnienie wszystkich dobrych i złych doświadczeń w zakresie cząsteczek, podczas gdy GSA został zmieniony na samodostosowujący, uwzględniając określony zakres dla niektórych parametrów, takich jak np. stała grawitacyjna i zestaw czynników o najlepszych wartościach sprawności. Optymalny rozmiar i wzmocnienie elementów zostały określone dzięki zastosowaniu techniki w środowisku komputerowym, w którym cały proces analizy, projektowania i optymalizacji został zakodowany w C++. Procedura analizy i projektowania przebiega zgodnie ze specyfikacjami kodów indyjskich. Okazało się, że zastosowanie samodostosowującego algorytmu wyszukiwania grawitacyjnego wraz z demokratyczną techniką optymalizacji roju cząsteczek zapewnia dwie wyraźne przewagi nad standardową PSO i GSA, a mianowicie lepszą zdolność do ucieczki od lokalnej optymalności i szybszy współczynnik konwergencji. Całe sformułowanie dla optymalnego projektu kosztów ramy obejmuje zarówno koszt belek i słupów. W tym podejściu, zmienne każdego elementu ramy konstrukcyjnej zostały uznane za funkcje ciągłe i zaokrąglone odpowiednio do zastosowania praktycznego znaczenia niniejszego badania. Rozważono kilka przykładów, które podkreślają ważność optymalnej procedury projektowania, a wyniki porównano z wcześniejszymi badaniami, w celu sprawdzenia ich skuteczności i efektywności. Proponowany algorytm pokonuje ograniczenia dwóch indywidualnych algorytmów, biorąc pod uwagę ich hybrydę, a tym samym poprawia ogólną wydajność. Wprowadzono niezbędne zmiany, aby badanie było zgodne z wcześniejszymi badaniami. Porównanie z innymi wcześniej stosowanymi technikami hybrydowymi pokazuje, że czas potrzebny na przeprowadzenie procesu optymalizacji w niniejszym badaniu – z wykorzystaniem techniki MPSOGSA – został znacznie zmniejszony. Ponadto, podczas projektowania ram RC obniżono całkowity koszt za pomocą techniki MPSOGSA. Obniżenie kosztów w obszarze stali odgrywa większą rolę w optymalizacji, w porównaniu do redukcji kosztów w przekroju poprzecznym elementów ramy, co zostało szczegółowo przeanalizowane na przykładzie.
Źródło:
Archives of Civil Engineering; 2017, 63, 4; 123-134
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Lung cancer detection using an integration of fuzzy K-Means clustering and deep learning techniques for CT lung images
Autorzy:
Prasad, J. Maruthi Nagendra
Chakravarty, S.
Krishna, M. Vamsi
Powiązania:
https://bibliotekanauki.pl/articles/2173683.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fuzzy K-means
artificial neural networks
SVM
support vector machine
crow search optimization algorithm
algorytm rozmytych k-średnich
sztuczne sieci neuronowe
maszyna wektorów wspierających
algorytm optymalizacji wyszukiwania kruków
Opis:
Computer aided detection systems are used for the provision of second opinion during lung cancer diagnosis. For early-stage detection and treatment false positive reduction stage also plays a vital role. The main motive of this research is to propose a method for lung cancer segmentation. In recent years, lung cancer detection and segmentation of tumors is considered one of the most important steps in the surgical planning and medication preparations. It is very difficult for the researchers to detect the tumor area from the CT (computed tomography) images. The proposed system segments lungs and classify the images into normal and abnormal and consists of two phases, The first phase will be made up of various stages like pre-processing, feature extraction, feature selection, classification and finally, segmentation of the tumor. Input CT image is sent through the pre-processing phase where noise removal will be taken care of and then texture features are extracted from the pre-processed image, and in the next stage features will be selected by making use of crow search optimization algorithm, later artificial neural network is used for the classification of the normal lung images from abnormal images. Finally, abnormal images will be processed through the fuzzy K-means algorithm for segmenting the tumors separately. In the second phase, SVM classifier is used for the reduction of false positives. The proposed system delivers accuracy of 96%, 100% specificity and sensitivity of 99% and it reduces false positives. Experimental results shows that the system outperforms many other systems in the literature in terms of sensitivity, specificity, and accuracy. There is a great tradeoff between effectiveness and efficiency and the proposed system also saves computation time. The work shows that the proposed system which is formed by the integration of fuzzy K-means clustering and deep learning technique is simple yet powerful and was effective in reducing false positives and segments tumors and perform classification and delivers better performance when compared to other strategies in the literature, and this system is giving accurate decision when compared to human doctor’s decision.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e139006
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Problem-Independent Approach to Multiprocessor Dependent Task Scheduling
Autorzy:
Król, D.
Zydek, D.
Koszałka, L.
Powiązania:
https://bibliotekanauki.pl/articles/226364.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
tasks scheduling
DAG
genetic algorithm
tabu search
makespan
Opis:
This paper concerns Directed Acyclic Graph task scheduling on parallel executors. The problem is solved using two new implementations of Tabu Search and genetic algorithm presented in the paper. A new approach to solution coding is also introduced and implemented in both metaheuristics algorithms. Results given by the algorithms are compared to those generated by greedy LPT and SS-FF algorithms; and HAR algorithm. The analysis of the obtained results of multistage simulation experiments confirms the conclusion that the proposed and implemented algorithms are characterized by very good performance and characteristics.
Źródło:
International Journal of Electronics and Telecommunications; 2012, 58, 4; 369-379
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Minimizing the Makespan and Total Tardiness in Hybrid Flow Shop Scheduling with Sequence-Dependent Setup Times
Autorzy:
Mousavi, Seyyed Mostafa
Shahnazari-Shahrezaei, Parisa
Powiązania:
https://bibliotekanauki.pl/articles/2201180.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
dispatching rule
genetic algorithm
hybrid flow shop
neighborhood search structure
Opis:
The paper considers the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the makespan and the total tardiness. The multi-objective genetic algorithm is applied to solve this problem, which belongs to the non-deterministic polynomial-time (NP)-hard class. In the structure of the proposed algorithm, the initial population, neighborhood search structures and dispatching rules are studied to achieve more efficient solutions. The performance of the proposed algorithm compared to the efficient algorithm available in literature (known as NSGA-II) is expressed in terms of the data envelopment analysis method. The computational results confirm that the set of efficient solutions of the proposed algorithm is more efficient than the other algorithm.
Źródło:
Management and Production Engineering Review; 2023, 14, 1; 13--24
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Improving the TSAB algorithm through parallel computing
Autorzy:
Rudy, Jarosław
Pempera, Jaroslaw
Smutnicki, Czesław
Powiązania:
https://bibliotekanauki.pl/articles/229535.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
job shop scheduling
parallel computing
operations research
taboo search
TSAB algorithm
coarse-grained parallelization
Opis:
In this paper, a parallel multi-path variant of the well-known TSAB algorithm for the job shop scheduling problem is proposed. Coarse-grained parallelization method is employed, which allows for great scalability of the algorithm with accordance to Gustafon’s law. The resulting P-TSAB algorithm is tested using 162 well-known literature benchmarks. Results indicate that P-TSAB algorithm with a running time of one minute on a modern PC provides solutions comparable to the ones provided by the newest literature approaches to the job shop scheduling problem. Moreover, on average P-TSAB achieves two times smaller percentage relative deviation from the best known solutions than the standard variant of TSAB. The use of parallelization also relieves the user from having to fine-tune the algorithm. The P-TSAB algorithm can thus beused as module in real-life production planning systems or as a local search procedure in other algorithms. It can also provide the upper bound of minimal cycle time for certain problems of cyclic scheduling.
Źródło:
Archives of Control Sciences; 2020, 30, 3; 411-435
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system
Autorzy:
Mostafa, Hazem H.
Ibrahim, Amr M.
Anis, Wagdi R.
Powiązania:
https://bibliotekanauki.pl/articles/141645.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid optimization
golden sections search
multi-verse optimization algorithm
maximum power point tracking
perturb and observe
photovoltaic (PV)
Opis:
This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS- PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.
Źródło:
Archives of Electrical Engineering; 2019, 68, 3; 611-627
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
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