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.


References in zbMATH (referenced in 24 articles )

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  1. Kronqvist, Jan; Lundell, Andreas; Westerlund, Tapio: The extended supporting hyperplane algorithm for convex mixed-integer nonlinear programming (2016)
  2. Petridis, Konstantinos: Optimal design of multi-echelon supply chain networks under normally distributed demand (2015)
  3. Hamzeei, Mahdi; Luedtke, James: Linearization-based algorithms for mixed-integer nonlinear programs with convex continuous relaxation (2014)
  4. Patil, Bhagyesh V.; Nataraj, P.S.V.: An improved Bernstein global optimization algorithm for MINLP problems with application in process industry (2014)
  5. D’ambrosio, Claudia; Lodi, Andrea: Mixed integer nonlinear programming tools: an updated practical overview (2013)
  6. Bonami, Pierre; Kilinç, Mustafa; Linderoth, Jeff: Algorithms and software for convex mixed integer nonlinear programs (2012)
  7. Kolb, Oliver; Morsi, Antonio; Lang, Jens; Martin, Alexander: Nonlinear and mixed integer linear programming (2012)
  8. D’Ambrosio, Claudia; Lodi, Andrea: Mixed integer nonlinear programming tools: a practical overview (2011)
  9. Salazar-Aguilar, María Angélica; Ríos-Mercado, Roger Z.; Cabrera-Ríos, Mauricio: New models for commercial territory design (2011)
  10. Günlük, Oktay; Linderoth, Jeff: Perspective reformulations of mixed integer nonlinear programs with indicator variables (2010)
  11. Karoonsoontawong, Ampol; Waller, Steven Travis: Integrated network capacity expansion and traffic signal optimization problem: Robust bi-level dynamic formulation (2010)
  12. Murray, Walter; Ng, Kien-Ming: An algorithm for nonlinear optimization problems with binary variables (2010)
  13. Taaffe, Kevin; Geunes, Joseph; Romeijn, H.Edwin: Supply capacity acquisition and allocation with uncertain customer demands (2010)
  14. Bonami, Pierre; Cornuéjols, Gérard; Lodi, Andrea; Margot, François: A feasibility pump for mixed integer nonlinear programs (2009)
  15. Bonami, Pierre; Biegler, Lorenz T.; Conn, Andrew R.; Cornuéjols, Gérard; Grossmann, Ignacio E.; Laird, Carl D.; Lee, Jon; Lodi, Andrea; Margot, François; Sawaya, Nicolas; Wächter, Andreas: An algorithmic framework for convex mixed integer nonlinear programs (2008)
  16. You, Peng-Sheng: An efficient computational approach for railway booking problems (2008)
  17. Sherali, Hanif D.; Ganesan, Vikram: An inverse reliability-based approach for designing under uncertainty with application to robust piston design (2007)
  18. Soleymani, S.; Ranjbar, A.M.; Shouraki, S.Bagheri; Shirani, A.R.; Sadati, N.: A new approach for bidding strategy of Gencos using particle swarm optimization combined with simulated annealing method (2007)
  19. Murray, Walter; Shanbhag, Uday V.: A local relaxation approach for the siting of electrical substations (2006)
  20. Sağlam, Burcu; Salman, F.Sibel; Sayın, Serpil; Türkay, Metin: A mixed-integer programming approach to the clustering problem with an application in customer segmentation (2006)

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