Multi-Objective Optimization of Mixed-Variable: Stochastic Systems Using Single-Objective Formulations
Paciencia, Todd J
ISBN 10: 128829204X ISBN 13: 9781288292042
Verlag: Biblioscholar, 2012
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Two new algorithms are presented for multi-objective optimization of mixed-variable, stochastic systems. Both are based off of prior algorithms, but combine those pre-exsting algorithms with several other methods, to include single-objective formulations, surrogates, n-dimensional visualizations, aspiration an reservation levels, and direct search methods. Results are shown for a test set of 13 problems, ranging from 2 to 8 objectives, and including non-convex, mixed-variable, and discontinuous problems.
Reseña del editor: Two new algorithms are presented for multi-objective optimization of mixed-variable, stochastic systems. Both are based off of prior algorithms, but combine those pre-exsting algorithms with several other methods, to include single-objective formulations, surrogates, n-dimensional visualizations, aspiration an reservation levels, and direct search methods. Results are shown for a test set of 13 problems, ranging from 2 to 8 objectives, and including non-convex, mixed-variable, and discontinuous problems.
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Titel: Multi-Objective Optimization of ...
Verlag: Biblioscholar
Erscheinungsdatum: 2012
Einband: Softcover
Zustand: New
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Multi-Objective Optimization of Mixed-Variable: Stochastic Systems Using Single-Objective Formulations
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Zustand: New. KlappentextrnrnTwo new algorithms are presented for multi-objective optimization of mixed-variable, stochastic systems. Both are based off of prior algorithms, but combine those pre-exsting algorithms with several other methods, to include singl. Artikel-Nr. 6553569
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Multi-Objective Optimization of Mixed-Variable: Stochastic Systems Using Single-Objective Formulations
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Creative Media Partners, LLC Nov 2012, 2012
ISBN 10: 128829204X
ISBN 13: 9781288292042
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Taschenbuch. Zustand: Neu. Neuware - Two new algorithms are presented for multi-objective optimization of mixed-variable, stochastic systems. Both are based off of prior algorithms, but combine those pre-exsting algorithms with several other methods, to include single-objective formulations, surrogates, n-dimensional visualizations, aspiration an reservation levels, and direct search methods. Results are shown for a test set of 13 problems, ranging from 2 to 8 objectives, and including non-convex, mixed-variable, and discontinuous problems. Artikel-Nr. 9781288292042
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