An integrated solver for optimization problems

Tallys Yunes, Ionuţ D. Aron, J. N. Hooker

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)342-356
Number of pages15
JournalOperations Research
Issue number2
StatePublished - Mar 2010


  • Constraint; modeling languages
  • Global
  • Integer
  • Integrated optimization
  • Nonlinear
  • Optimization
  • Production: planning and product configuration
  • Programming: linear
  • Scheduling: parallel machines

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research


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