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The Arrow cluster and our 22 CPLEX licenses were funded under a CFI grant. This grant requires us to complete annual reports explaining how this infrastructure is being used. If you use the cluster or CPLEX licenses for a project, large or small, please enter a bullet item here that gives a short description of your project and the role the cluster played. If you used these resources for multiple projects and/or for a period of time that spans the time periods given here, please create multiple bullets. |
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- TAC SCM: Used CPLEX's MILP solver to schedule production and deliveries for a SCM scenario (Sept 2006 - on going; Erik Zawadzki, CS)
- Exact regularization of convex programs: I used CPLEX (thanks, Kevin!) for the numerical results of a paper (see reference below). This paper gives the most general conditions possible under which a general convex program (eg, linear, quadratic, semidefinite, second-order cone, etc) can be regularized, and a solution of the original problem still be obtained.
- Michael P. Friedlander and Paul Tseng, Exact regularization of convex programs
 , To appear in SIAM Journal on Optimization. Also listed as Dept. of Computer Science Tech. Rept. TR-2006-26, November 2006 (revised April 2007).
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- Empirical hardness model for SAT: Using arrow cluster, we collect SAT solvers’ runtimes data and problem instances’ features data. Empirical hardness models are trained to predict a solver’s runtime for a given problem instance based on instance’s features. We can also predict the satisfiability for an instance based on those features.(May 2006 - ongoing; Lin Xu, Holger H. Hoos and Kevin Leyton-Brown, CS)
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-- KevinLeytonBrown - 05 May 2007 |
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