Mixed Integer Nonlinear Programming

Mixed Integer Nonlinear Programming | Springer



​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.

Herausgeber Springer
Autor(en) Sven Leyffer, Jon Lee
ISBN 978-1-4614-1926-6
veröffentlicht 2012
Seiten 690
Sprache English

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