An Integrated Solver for Optimization Problems

  • Authors:

  • Tallys Yunes;Ionuţ D. Aron;J. N. Hooker

  • Affiliations:

  • Department of Management Science, School of Business Administration, University of Miami, Coral Gables, Florida 33124;WorldQuant LLC, New York, New York 10103;Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213

  • Venue:
  • Operations Research
  • Year:
  • 2010

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Abstract

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, constraint programming, and global optimization 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. Nevertheless, integration often requires special-purpose coding, which is time consuming and error prone. We present a general-purpose solver, SIMPL, that allows its user to replicate (and sometimes improve on) the results of custom implementations with concise models written in a high-level language. We apply SIMPL to production planning, product configuration, machine scheduling, and truss structure design problems on which customized integrated methods have shown significant computational advantage. We obtain results that either match or surpass the original codes at a fraction of the implementation effort.