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On the design of R-based scalable frameworks for data science applications
Theußl, Stefan Peter - 2020
Persistent link: https://www.econbiz.de/10012194139
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Scalable parallel nonlinear optimization with pynumero and parapint
Rodriguez, Jose S.; Parker, Robert; Laird, Carl D.; … - In: INFORMS journal on computing : JOC ; charting new … 35 (2023) 2, pp. 509-517
Persistent link: https://www.econbiz.de/10014327652
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Integer and nonlinear programming
Abadie, Jean (ed.); Wolfe, P. (contributor) - 1970
Persistent link: https://www.econbiz.de/10000061302
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Reduction methods in nonlinear programming
Hoek, Gerard van der - 1980
Persistent link: https://www.econbiz.de/10000071788
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Nonlinear and dynamic programming : an introduction
Danø, Sven - 1975
Persistent link: https://www.econbiz.de/10000048286
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Algorithmic approximation of optimal value differential stability bounds in nonlinear programming
Hutzler, William P. - 1981
Persistent link: https://www.econbiz.de/10000011105
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Nonlinear programming : theory and methods
Martos, Béla - 1975
Persistent link: https://www.econbiz.de/10000029505
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High level modeling systems and nonlinear programming
Brooke, Anthony - 1984
Persistent link: https://www.econbiz.de/10003143331
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Modeling systems and nonlinear programming in a research environment
Brooke, Anthony - 1985
Persistent link: https://www.econbiz.de/10003187651
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CONOPT, a GRG-code for large sparse dynamic nonlinear optimization problems
Drud, Arne - 1983
Persistent link: https://www.econbiz.de/10002097242