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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Mixed Integer Nonlinear Programming

Mixed Integer Nonlinear Programming

Lee, Jon
Leyffer, Sven

Hardcover

Series: IMA Volumes in Mathematics and Its Applications, Book 154

General MathematicsProgramming

ISBN10: 1461419263
ISBN13: 9781461419266
Publisher: Springer Nature
Published: Dec 1 2011
Pages: 692
Weight: 2.57
Height: 1.50 Width: 6.14 Depth: 9.21
Language: English
Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners -- including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers -- are interested in solving large-scale MINLP instances.

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