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- W2408622691 abstract "We present an approach for improving the performance of combinatorial optimization algorithms by generating an optimal Parallel Portfolio of Algorithms (PPA). A PPA is a collection of diverse algorithms for solving a single problem, all running concurrently on a single processor until a solution is produced. The performance of the portfolio may be controlled by assigning different shares of processor time to each algorithm. We present a method for finding a static PPA, in which the share of processor time allocated to each algorithm is fixed. The schedule is shown to be optimal with respect to a given training set of instances. We draw bounds on the performance of the PPA over random instances and evaluate the performance empirically on a collection of 23 state-of-the-art SAT algorithms. The results show significant performance gains (up to a factor of 2) over the fastest individual algorithm in a realistic setting." @default.
- W2408622691 created "2016-06-24" @default.
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- W2408622691 date "2006-01-01" @default.
- W2408622691 modified "2023-09-26" @default.
- W2408622691 title "Learning Static Parallel Portfolios of Algorithms." @default.
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