This study presents application of genetic algorithm and particle swarm optimization techniques to estimate optimal weight of two truss structures, two-dimensional and three-dimensional truss, satisfying a constrained displacement and allowable stress. Constraints are mostly handled by using the concept of penalty functions. Two strategies of penalty functions, exterior penalty function strategy (EPFS) and self–organizing adaptive penalty strategy (SOAPS), are used in turn to combine with mass function to become objective function of optimization problems. This study proposes the comparison of efficiency and convenience between two penalty function strategies, EPFS and SOAPS, as well as the result of optimal weight for truss structure between genetic algorithm and particle swarm optimization.
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Condición: New. PRINT ON DEMAND pp. 88. Nº de ref. del artículo: 18391778079
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This study presents application of genetic algorithm and particle swarm optimization techniques to estimate optimal weight of two truss structures, two-dimensional and three-dimensional truss, satisfying a constrained displacement and allowable stress. Constraints are mostly handled by using the concept of penalty functions. Two strategies of penalty functions, exterior penalty function strategy (EPFS) and self-organizing adaptive penalty strategy (SOAPS), are used in turn to combine with mass function to become objective function of optimization problems. This study proposes the comparison of efficiency and convenience between two penalty function strategies, EPFS and SOAPS, as well as the result of optimal weight for truss structure between genetic algorithm and particle swarm optimization. 88 pp. Englisch. Nº de ref. del artículo: 9786203573992
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Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Nguyen Pham The NhanPham The Nhan NGUYEN is a lecturer of manufacturing division of Faculty of Mechanical engineering, University of science and technology, the University of Danang, Vietnam. He received his MS degree from Dongguk Un. Nº de ref. del artículo: 467237602
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Taschenbuch. Condición: Neu. Neuware -This study presents application of genetic algorithm and particle swarm optimization techniques to estimate optimal weight of two truss structures, two-dimensional and three-dimensional truss, satisfying a constrained displacement and allowable stress. Constraints are mostly handled by using the concept of penalty functions. Two strategies of penalty functions, exterior penalty function strategy (EPFS) and self¿organizing adaptive penalty strategy (SOAPS), are used in turn to combine with mass function to become objective function of optimization problems. This study proposes the comparison of efficiency and convenience between two penalty function strategies, EPFS and SOAPS, as well as the result of optimal weight for truss structure between genetic algorithm and particle swarm optimization.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. Nº de ref. del artículo: 9786203573992
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This study presents application of genetic algorithm and particle swarm optimization techniques to estimate optimal weight of two truss structures, two-dimensional and three-dimensional truss, satisfying a constrained displacement and allowable stress. Constraints are mostly handled by using the concept of penalty functions. Two strategies of penalty functions, exterior penalty function strategy (EPFS) and self-organizing adaptive penalty strategy (SOAPS), are used in turn to combine with mass function to become objective function of optimization problems. This study proposes the comparison of efficiency and convenience between two penalty function strategies, EPFS and SOAPS, as well as the result of optimal weight for truss structure between genetic algorithm and particle swarm optimization. Nº de ref. del artículo: 9786203573992
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