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A Parallel Genetic Algorithm for the Open-Shop Scheduling Problem Using Deterministic and Random Moves

Steve Bou Ghosn, Fouad Drouby, Haidar M. Harmanani


This paper investigates the use of parallel genetic algorithms in order to solve the open-shop scheduling problem. The method is based on a novel implementation of genetic operators that combines the use of deterministic and random moves. The method is implemented using MPI on a Beowulf cluster. Comparisons using the Taillard benchmarks give favorable results for this algorithm.


Open-shop scheduling, parallel genetic algorithms.

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