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, Belotti, Pietro |
---|---|
Other Authors: | Sloan School of Management |
Format: | Article |
Language: | English |
Published: |
Springer Berlin Heidelberg
2016
|
Online Access: | http://hdl.handle.net/1721.1/105215 |
Similar Items
-
A feasible path-based branch and bound algorithm for strongly nonconvex MINLP problems
by: Chao Liu, et al.
Published: (2022-09-01) -
Heuristic Methods Based on MINLP Formulation for Reliable Capacitated Facility Location Problems
by: Mohammad Rohaninejad, et al.
Published: (2015-09-01) -
Solving the nonlinear discrete transportation problem by MINLP optimization
by: Uroš Klanšek
Published: (2014-03-01) -
Sufficient pruning conditions for MINLP in gas network design
by: Jesco Humpola, et al.
Published: (2017-03-01) -
The MINLP Approach to Topology, Shape and Discrete Sizing Optimization of Trusses
by: Simon Šilih, et al.
Published: (2022-01-01)