A recipe for finding good solutions to MINLPs

  • Finding good (or even just feasible) solutions forMixed-Integer Nonlinear Programming problems independently of the specific problem structure is a very hard but practically important task, especially when the objective and/or the constraints are nonconvex. With this goal in mind, we present a general-purpose heuristic based on Variable Neighborhood Search, Local Branching, a local Nonlinear Programming algorithm and Branch-and-Bound.We test the proposed approach on MINLPLib, comparing with several existing heuristic and exact methods. An implementation of the proposed heuristic is freely available and can employ all NLP/MINLP solvers with an AMPL interface as the main search tools.

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Metadaten
Author:Leo Liberti, Nenad Mladenović, Giacomo Nannicini
DOI:https://doi.org/10.1007/s12532-011-0031-y
ISSN:1867-2949
Parent Title (English):Mathematical Programming Computation
Publisher:Springer Science and Business Media LLC
Document Type:Article
Language:English
Year of Completion:2011
Tag:Software; Theoretical Computer Science
Volume:3
Issue:4
Page Number:42
First Page:349
Last Page:390
Mathematical Programming Computation :MPC 2011 - Issue 4
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