Rounding-based heuristics for nonconvex MINLPs
We propose two primal heuristics for nonconvex mixed-integer nonlinear programs. Both are based on the idea of rounding the solution of a continuous nonlinear program subject to linear constraints. Each rounding step is accomplished through the solution of a mixed-integer linear program. Our heurist...
Main Authors: | Nannicini, Giacomo (Contributor), Belotti, Pietro (Author) |
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Other Authors: | Sloan School of Management (Contributor) |
Format: | Article |
Language: | English |
Published: |
Springer Berlin Heidelberg,
2016-11-04T20:33:54Z.
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Subjects: | |
Online Access: | Get fulltext |
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