During the past decades, optimization has become a very important research topic for engineers and also for scientists. Optimization techniques have been becoming one of the most important factors in obtaining the most optimal solution for solving the problem in Construction, Industrial, Mechanical, and other engineering fields. This research proposes a hybrid model of a new and adopted searching algorithm from Computer Science, named Grover Algorithm with one of new established meta-heuristic algorithm, RSSA (Reduced Space Searching Algorithm). The combination of both algorithms is validated by solving multiple peak functions. The traditional Genetic Algorithm (GA) is used as a standard of comparison in appraising the RSSA-Grover result. Simulation result shows that RSSA-Grover performed better than GA due to its accuracy. Furthermore, this proposed algorithm is successfully applied to solve the real case of Tower Crane location selection, whose objective is to find the minimum duration due to cost minimizing, concealed by abundant constraints and decision variables.
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Evan Subrata, ST, M.Sc.Eng.: Studied Structural Engineering at Institut Teknologi Bandung for Bachelor Degree and continued with Construction Management and IT at National Taiwan University of Science and Technology for Master Degree. Project Engineer at Jardine Schindler Group, Singapore.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -During the past decades, optimization has become a very important research topic for engineers and also for scientists. Optimization techniques have been becoming one of the most important factors in obtaining the most optimal solution for solving the problem in Construction, Industrial, Mechanical, and other engineering fields. This research proposes a hybrid model of a new and adopted searching algorithm from Computer Science, named Grover Algorithm with one of new established meta-heuristic algorithm, RSSA (Reduced Space Searching Algorithm). The combination of both algorithms is validated by solving multiple peak functions. The traditional Genetic Algorithm (GA) is used as a standard of comparison in appraising the RSSA-Grover result. Simulation result shows that RSSA-Grover performed better than GA due to its accuracy. Furthermore, this proposed algorithm is successfully applied to solve the real case of Tower Crane location selection, whose objective is to find the minimum duration due to cost minimizing, concealed by abundant constraints and decision variables. 96 pp. Englisch. Codice articolo 9783838376417
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -During the past decades, optimization has become a very important research topic for engineers and also for scientists. Optimization techniques have been becoming one of the most important factors in obtaining the most optimal solution for solving the problem in Construction, Industrial, Mechanical, and other engineering fields. This research proposes a hybrid model of a new and adopted searching algorithm from Computer Science, named Grover Algorithm with one of new established meta-heuristic algorithm, RSSA (Reduced Space Searching Algorithm). The combination of both algorithms is validated by solving multiple peak functions. The traditional Genetic Algorithm (GA) is used as a standard of comparison in appraising the RSSA-Grover result. Simulation result shows that RSSA-Grover performed better than GA due to its accuracy. Furthermore, this proposed algorithm is successfully applied to solve the real case of Tower Crane location selection, whose objective is to find the minimum duration due to cost minimizing, concealed by abundant constraints and decision variables.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch. Codice articolo 9783838376417
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - During the past decades, optimization has become a very important research topic for engineers and also for scientists. Optimization techniques have been becoming one of the most important factors in obtaining the most optimal solution for solving the problem in Construction, Industrial, Mechanical, and other engineering fields. This research proposes a hybrid model of a new and adopted searching algorithm from Computer Science, named Grover Algorithm with one of new established meta-heuristic algorithm, RSSA (Reduced Space Searching Algorithm). The combination of both algorithms is validated by solving multiple peak functions. The traditional Genetic Algorithm (GA) is used as a standard of comparison in appraising the RSSA-Grover result. Simulation result shows that RSSA-Grover performed better than GA due to its accuracy. Furthermore, this proposed algorithm is successfully applied to solve the real case of Tower Crane location selection, whose objective is to find the minimum duration due to cost minimizing, concealed by abundant constraints and decision variables. Codice articolo 9783838376417
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Hybrid Model of Optimization Algorithms: Concept and Derivation | Model Application in Optimizing Time and Cost of Tower Crane Complexity | Evan Subrata | Taschenbuch | 96 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838376417 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 101028608
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Da: Mispah books, Redhill, SURRE, Regno Unito
Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA75838383764126
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