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Wyświetlanie 1-8 z 8
Tytuł:
Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part II. Computational simulations
Autorzy:
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/260598.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
Opis:
Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems of the four areas and giving an effective solution of the problem. So far, a significant progress towards the solution of the problem has not been obtained. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area on a high speed vehicle-passenger catamaran structure, with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members, taken into account. Details of the computational models were at the level typical for conceptual design. Scantlings were analyzed by using selected rules of a classification society. The results of numerical experiments with the use of the developed algorithm, are presented. They show that the proposed genetic algorithm can be an efficient tool for multi-objective optimization of ship structures. The paper is published in three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational investigations, and Part III: Analysis of the results.
Źródło:
Polish Maritime Research; 2011, 3; 3-30
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part I. Theoretical background on evolutionary multi objective optimization
Autorzy:
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/259303.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
set of non-dominated solutions
Opis:
Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimal structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from these four areas and giving an effective solution of this problem. So far, a significant progress towards the solution of this problem has not been obtained. An objective of the present paper was to develop an evolutionary algorithm for multi-objective optimization of the structural elements of the large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in details. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area on a high speed vehicle-passenger catamaran structure with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinals and transversal members. Details of the computational models were at the level typical for conceptual design. Scantlings were analyzed using the selected rules of a classification society. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm can be an efficient multi-objective optimization tool for ship structures optimization. The paper will be published in three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational investigations, and Part III: Analysis of the results.
Źródło:
Polish Maritime Research; 2011, 2; 3-18
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part II. Analysis of the results
Autorzy:
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/260079.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
set of non-dominated solutions
Opis:
Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from the four areas and giving an effective solution of the problem. Any significant progress towards solving the problem has not been obtained so far. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of the structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area for a high - speed vehicle-passenger catamaran structure, with taking into account several design variables such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members. Details of the computational models were kept at the level typical for conceptual design stage. Scantlings were analyzed by using the selected classification society rules. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm may be considered an efficient tool for multi-objective optimization of ship structures. The paper has been published in the three parts: Part I: Theoretical background on evolutionary multiobjective optimization, Part II: Computational simulations, and Part III: Analysis of the results.
Źródło:
Polish Maritime Research; 2011, 4; 3-13
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptive robust PID sliding control of a liquid level system based on multi-objective genetic algorithm optimization
Autorzy:
Mahmoodabadi, M. J.
Taherkhorsandi, M.
Talebipour, M.
Powiązania:
https://bibliotekanauki.pl/articles/206697.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
sliding mode control
PID control
adaptive control
genetic algorithm
multi-objective optimization
liquid level system
Opis:
Adaptive robust PID sliding mode control optimized by means of multi-objective genetic algorithm is presented in this paper to control a three-tank liquid level system with external disturbances. While PID constitutes a reliable and stable controller, when compared to sliding mode control (SMC); robustness and tracking performance of SMC are higher than those of the PID control. To use the unique features of both controllers, optimal sliding mode control is executed in terms of a supervisory controller to enhance the performance of optimal adaptive PID control and to provide the necessary control inputs. After the design of the control law, control coefficients of all four involved controllers are optimized by using the multi-objective genetic algorithm so as to minimize errors and the input of the controller. Simulations illustrate that the adaptive robust PID sliding controller based on multi-objective genetic algorithm optimization provides a superior response in comparison to the results obtained separately by PID control, sliding mode control, and adaptive PID control, respectively.
Źródło:
Control and Cybernetics; 2017, 46, 3; 227-246
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization
Autorzy:
Patel, G. C. M.
Krishna, P.
Vundavilli, P. R.
Parappagoudar, M. B.
Powiązania:
https://bibliotekanauki.pl/articles/379601.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
squeeze casting process
multi-objective optimization
genetic algorithm
squeeze casting
prasowanie stopu
optymalizacja wielokryterialna
algorytm genetyczny
Opis:
The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.). It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature) combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength) due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA), particle swarm optimization (PSO) and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD) methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.
Źródło:
Archives of Foundry Engineering; 2016, 16, 3; 172-186
1897-3310
2299-2944
Pojawia się w:
Archives of Foundry Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Objective Optimization of Motor Vessel Route
Autorzy:
Marie, S.
Courteille, E.
Powiązania:
https://bibliotekanauki.pl/articles/117604.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
route planning
Optimization of Vessel Route
multi-objective optimization
Motor Vessel
Optimal Route
Multi-Objective Genetic Algorithm (MOGA)
Bézier Curve
MATLAB
Opis:
This paper presents an original method that allows computation of the optimal route of a motor vessel by minimizing its fuel consumption. The proposed method is based on a new and efficient meshing procedure that is used to define a set of possible routes. A consumption prediction tool has been developed in order to estimate the fuel consumption along a given trajectory. The consumption model involves the effects of the meteorological conditions, the shape of the hull and the power train characteristics. Pareto-optimization with a Multi-Objective Genetic Algorithm (MOGA) is taken as a framework for the definition and the solution of the multi-objective optimization problem addressed. The final goal of this study is to provide a decision helping tool giving the route that minimizes the fuel consumption in a limited or optimum time.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2009, 3, 2; 133-141
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
System reliability optimization: A fuzzy multi-objective genetic algorithm approach
Optymalizacja niezawodności systemu: metoda rozmytego algorytmu genetycznego do optymalizacji wielokryterialnej
Autorzy:
Mutingi, M.
Powiązania:
https://bibliotekanauki.pl/articles/300808.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
system reliability optimization
multi-objective optimization
genetic algorithm
fuzzy optimization
redundancy
optymalizacja niezawodności systemu
optymalizacja wielokryterialna
algorytm genetyczny
optymalizacja rozmyta
nadmiarowość
Opis:
System reliability optimization is often faced with imprecise and conflicting goals such as reducing the cost of the system and improving the reliability of the system. The decision making process becomes fuzzy and multi-objective. In this paper, we formulate the problem as a fuzzy multi-objective nonlinear program. A fuzzy multi-objective genetic algorithm approach (FMGA) is proposed for solving the multi-objective decision problem in order to handle the fuzzy goals and constraints. The approach is able flexible and adaptable, allowing for intermediate solutions, leading to high quality solutions. Thus, the approach incorporates the preferences of the decision maker concerning the cost and reliability goals through the use of fuzzy numbers. The utility of the approach is demonstrated on benchmark problems in the literature. Computational results show that the FMGA approach is promising.
Często spotykanym problemem w optymalizacji niezawodności systemu są niedokładnie określone i sprzeczne cele, takie jak zmniejszenie kosztów systemu przy jednoczesnej poprawie jego niezawodności. Proces podejmowania decyzji staje się wtedy rozmyty i wielokryterialny. W niniejszej pracy, sformułowaliśmy ten problem jako rozmyty wielokryterialny program nieliniowy (FMOOP). Zaproponowaliśmy metodę rozmytego wielokryterialnego algorytmu genetycznego (FMGA), która pozwala rozwiązać wielokryterialny problem decyzyjny z uwzględnieniem rozmytych celów i ograniczeń. Podejście to jest uniwersalne, co pozwala na rozwiązania pośrednie, prowadzące do rozwiązań wysokiej jakości. Metoda uwzględnia preferencje decydenta w zakresie celów związanych z kosztami i niezawodnością poprzez wykorzystanie liczb rozmytych. Użyteczność FMGA wykazano na przykładzie wzorcowych problemów z literatury. Wyniki obliczeń wskazują, że podejście FMGA jest obiecujące.
Źródło:
Eksploatacja i Niezawodność; 2014, 16, 3; 400-406
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Generalized route planning approach for hazardous materials transportation with equity consideration
Autorzy:
Chai, H.
He, R.-C.
Jia, X.-yan
Ma, Ch.-x
Dai, C.-jie
Powiązania:
https://bibliotekanauki.pl/articles/223759.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hazardous materials transportation
transportation
route optimization
risk equity
multi-objective optimization
NSGA-II algorithm
genetic algorithm
transport materiałów niebezpiecznych
materiały niebezpieczne
optymalizacja trasy
kapitał własny
optymalizacja wielokryterialna
algorytm NSGA-II
algorytm genetyczny
Opis:
Hazardous materials transportation should consider risk equity and transportation risk and cost. In the hazardous materials transportation process, we consider risk equity as an important condition in optimizing vehicle routing for the long-term transport of hazardous materials between single or multiple origin-destination pairs (O-D) to reduce the distribution difference of hazardous materials transportation risk over populated areas. First, a risk equity evaluation scheme is proposed to reflect the risk difference among the areas. The evaluation scheme uses standard deviation to measure the risk differences among populated areas. Second, a risk distribution equity model is proposed to decrease the risk difference among populated areas by adjusting the path frequency between O-D pairs for hazardous materials transportation. The model is converted into two sub models to facilitate decision-making, and an algorithm is provided for each sub model. Finally, we design a numerical example to verify the accuracy and rationality of the model and algorithm. The numerical example shows that the proposed model is essential and feasible for reducing the complexity and increasing the portability of the transportation process.
Źródło:
Archives of Transport; 2018, 46, 2; 33-46
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-8 z 8

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