DICOPT
DICOPT is a program for solving mixed-integer nonlinear programming (MINLP) problems that involve linear binary or integer variables and linear and nonlinear continuous variables. While the modeling and solution of these MINLP optimization problems has not yet reached the stage of maturity and reliability as linear, integer or non-linear programming modeling, these problems have a rich area of applications. For example, they often arise in engineering design, management sciences, and ﬁnance. DICOPT (DIscrete and Continuous OPTimizer) was developed by J. Viswanathan and Ignacio E. Grossmann at the Engineering Design Research Center (EDRC) at Carnegie Mellon University. The program is based on the extensions of the outer-approximation algorithm for the equality relaxation strategy. The MINLP algorithm inside DICOPT solves a series of NLP and MIP sub-problems. These sub-problems can be solved using any NLP (Nonlinear Programming) or MIP (Mixed-Integer Programming) solver that runs under GAMS.
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References in zbMATH (referenced in 35 articles )
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- Bernal, David E.; Vigerske, Stefan; Trespalacios, Francisco; Grossmann, Ignacio E.: Improving the performance of DICOPT in convex MINLP problems using a feasibility pump (2020)
- Kronqvist, Jan; Bernal, David E.; Grossmann, Ignacio E.: Using regularization and second order information in outer approximation for convex MINLP (2020)
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- Furini, Fabio; Traversi, Emiliano; Belotti, Pietro; Frangioni, Antonio; Gleixner, Ambros; Gould, Nick; Liberti, Leo; Lodi, Andrea; Misener, Ruth; Mittelmann, Hans; Sahinidis, Nikolaos V.; Vigerske, Stefan; Wiegele, Angelika: QPLIB: a library of quadratic programming instances (2019)
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- Schweidtmann, Artur M.; Mitsos, Alexander: Deterministic global optimization with artificial neural networks embedded (2019)
- Kronqvist, Jan; Lundell, Andreas; Westerlund, Tapio: The extended supporting hyperplane algorithm for convex mixed-integer nonlinear programming (2016)
- Petridis, Konstantinos: Optimal design of multi-echelon supply chain networks under normally distributed demand (2015)
- Hamzeei, Mahdi; Luedtke, James: Linearization-based algorithms for mixed-integer nonlinear programs with convex continuous relaxation (2014)
- Hijazi, Hassan; Bonami, Pierre; Ouorou, Adam: An outer-inner approximation for separable mixed-integer nonlinear programs (2014)
- Patil, Bhagyesh V.; Nataraj, P. S. V.: An improved Bernstein global optimization algorithm for MINLP problems with application in process industry (2014)
- D’ambrosio, Claudia; Lodi, Andrea: Mixed integer nonlinear programming tools: an updated practical overview (2013)
- Müller, Juliane; Shoemaker, Christine A.; Piché, Robert: SO-MI: a surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems (2013)
- Bonami, Pierre; Kilinç, Mustafa; Linderoth, Jeff: Algorithms and software for convex mixed integer nonlinear programs (2012)
- Canbolat, Mustafa S.; Wesolowsky, George O.: A planar single facility location and border crossing problem (2012)
- Kolb, Oliver; Morsi, Antonio; Lang, Jens; Martin, Alexander: Nonlinear and mixed integer linear programming (2012)
- D’Ambrosio, Claudia; Lodi, Andrea: Mixed integer nonlinear programming tools: a practical overview (2011)
- Salazar-Aguilar, María Angélica; Ríos-Mercado, Roger Z.; Cabrera-Ríos, Mauricio: New models for commercial territory design (2011)
- Günlük, Oktay; Linderoth, Jeff: Perspective reformulations of mixed integer nonlinear programs with indicator variables (2010)