Asgeir Tomasgard (NTNU, Norway)

Nonconvex generalized Benders decomposition for stochastic separable mixed-integer nonlinear programs
Wednesday 6 March 2013 at 15.30, JCMB 6206


This paper considers deterministic global optimization of scenario-based, two-stage stochastic mixed-integer nonlinear programs (MINLPs) in which the participating functions are nonconvex and separable in integer and continuous variables. A novel decomposition method based on generalized Benders decomposition, named nonconvex generalized Benders decomposition (NGBD), is developed to obtain ε-optimal solutions of the stochastic MINLPs of interest in finite time. The computational advantage of NGBD over state-of-the-art global optimizers is demonstrated through the computational study of several engineering problems from the natural gas sector.

Seminars by year

Current 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996