Tuesday, May 21
2:45-4:25 PM
Salon B
MS26
Progress in Mixed-Integer Nonlinear Programming
Many practical problems in process synthesis and process optimization lead to mathematical optimization models in continuous and discrete variables with nonlinear constraints. An enormous increase in the capabilities for solving either nonlinear programming problems or mixed integer linear programming problems has occurred in the last several years. The speakers will discuss recent work to design algorithms and software for solving mixed integer nonlinear programming problems (MINLP).
Organizer: Gerhard Reinelt,
Universit,t Heidelberg, Germany
- Cutting Planes, Revisited
- Sebastian Ceria, Columbia University
- Generalized Disjunctive Programming Algorithms for Nonlinear Discrete-
Continuous Optimization
- Ignacio E. Grossmann, M. Turkay, and A. Vecchietti, Carnegie Mellon University
- Computational Experiments of an Interior-Point Algorithm in a Parallel Branch-and-Cut Framework
- Eva K. Lee, Columbia University; and John Mitchell, Rensselaer Polytechnic Institute
MEM, 3/18/96