A penalty approach for solving nonsmooth and nonconvex MINLP problems
This paper presents a penalty approach for globally solving nonsmooth and nonconvex mixed-integer nonlinear programming (MINLP) problems. Both integrality constraints and general nonlinear constraints are handled separately by hyperbolic tangent penalty functions. Proximity from an iterate to a feas...
Autor principal: | |
---|---|
Outros Autores: | , |
Formato: | conferencePaper |
Idioma: | eng |
Publicado em: |
2018
|
Assuntos: | |
Texto completo: | http://hdl.handle.net/1822/55224 |
País: | Portugal |
Oai: | oai:repositorium.sdum.uminho.pt:1822/55224 |
Resumo: | This paper presents a penalty approach for globally solving nonsmooth and nonconvex mixed-integer nonlinear programming (MINLP) problems. Both integrality constraints and general nonlinear constraints are handled separately by hyperbolic tangent penalty functions. Proximity from an iterate to a feasible promising solution is enforced by an oracle penalty term. The numerical experiments show that the proposed oracle-based penalty approach is effective in reaching the solutions of the MINLP problems and is competitive when compared with other strategies. |
---|