Branch-and-price for a class of nonconvex mixed-integer nonlinear programs

This work attempts to combine the strengths of two major technologies that have matured over the last three decades: global mixed-integer nonlinear optimization and branch-and-price. We consider a class of generally nonconvex mixed-integer nonlinear programs (MINLPs) with linear complicating constra...

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Bibliographic Details
Published in:	Journal of global optimization Vol. 81; no. 4; pp. 861 - 880
Main Authors:	Allman, Andrew, Zhang, Qi
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.12.2021 Springer Springer Nature B.V
Subjects:	Algorithms Approximation Computer Science Decomposition Integer programming Linear programming Mathematics Mathematics and Statistics Mixed integer Operations Research/Decision Theory Optimization Real Functions Decomposition Nonconvex optimization Branch-and-price Mixed-integer nonlinear programming
ISSN:	0925-5001, 1573-2916
Online Access:	Get full text
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