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An integrated solver for optimization problems (2009)
| Citations: | 9 - 2 self |
BibTeX
@TECHREPORT{Yunes09anintegrated,
author = {Tallys Yunes and J. N. Hooker and Ionut D. Aron},
title = {An integrated solver for optimization problems},
institution = {},
year = {2009}
}
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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. 1
Keyphrases
optimization problem single system product configuration integrated problem machine scheduling concise model implementation effort original code significant computational advantage past several year central trend mixed integer linear programming right combination general-purpose solver special purpose coding general purpose solver high-level language different technology steady improvement truss structure design problem logical next step custom implementation optimization community recent research production planning constraint programming global optimization
