INFORMS Journal on Computing
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INFORMS JOURNAL ON COMPUTING
Vol. 21, No. 3, Summer 2009, pp. 349-362
DOI: 10.1287/ijoc.1090.0340
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Grid-Enabled Optimization with GAMS

Michael R. Bussieck, Michael C. Ferris, Alexander Meeraus

GAMS Software GmbH, 50933 Cologne, Germany
Computer Sciences Department, University of Wisconsin–Madison, Wisconsin 53706
GAMS Development Corporation, Washington, DC 20007

mbussieck{at}gams.com
ferris{at}cs.wisc.edu
ameeraus{at}gams.com

We describe a framework for modeling optimization problems for solution on a grid computer. The framework is easy to adapt to multiple grid engines and can seamlessly integrate evolving mechanisms from particular computing platforms. It facilitates the widely used master-worker model of computing and is shown to be flexible and powerful enough for a large variety of optimization applications. In particular, we summarize a number of new features of the GAMS modeling system that provide a lightweight, portable, and powerful framework for optimization on a grid. We provide downloadable examples of its use for embarrasingly parallel financial applications, decomposition of complementarity problems, and for solving very difficult mixed-integer programs to optimality. Computational results are provided for a number of different grid engines, including multicore machines, a pool of machines controlled by the Condor resource manager, and the grid engine from Sun Microsystems.

Key words: algebraic modeling language; grid computing; decomposition
History: received September 2007; revised September 2008; accepted February 2009.




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M. C. Ferris, C. T. Maravelias, and A. Sundaramoorthy
Simultaneous Batching and Scheduling Using Dynamic Decomposition on a Grid
INFORMS Journal on Computing, July 1, 2009; 21(3): 398 - 410.
[Abstract] [PDF]




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