WORKING PAPER WPS-MAS-08-01 Department of Management Science School of Business Administration, University of Miami Coral Gables, FL 33124-8237 Created: December 2005 Last update: July 2008 An Integrated Solver for Optimization Problems Ionut ¸ D. Aron ionut.aron@gmail.com John Hooker Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, john@hooker.tepper.cmu.edu Tallys Yunes Department of Management Science, School of Business Administration, University of Miami, Coral Gables, FL 33124-8237, tallys@miami.edu One of the central trends in the optimization community over the past several years has been the steady improvement of general-purpose solvers. A logical next step in this evolution is to combine mixed integer linear programming, global optimization, and constraint programming in a single system. Recent research in the area of integrated problem solving suggests that the right combination of different technologies can simplify modeling and speed up computation substantially. In this paper we address this goal by presenting a general purpose solver, SIMPL, that achieves low-level integration of solution techniques with a high-level modeling language. We apply SIMPL to production planning, product configuration, and machine scheduling problems on which customized integrated methods have shown significant computational advantage. We find that SIMPL can allow the user to obtain the same or greater advantage by writing concise models for a general-purpose solver. We also solve pooling, distillation, and heat exchanger network design problems to demonstrate how global optimization fits into SIMPL’s framework. Subject classifications : Programming: linear, nonlinear, integer and constraint programming; modeling languages; global optimization; integrated optimization. Production: planning and product configuration. Scheduling: parallel machines. 1