Parallel Genetic Algorithms for University Scheduling Problem

Artan Berisha, Eliot Bytyçi, Ardeshir Tershnjaku


University scheduling timetabling problem, falls into NP hard problems. Re-searchers have tried with many techniques to find the most suitable and fastest way for solving the problem. With the emergence of multi-core systems, the parallel implementation was considered for finding the solution. Our approaches attempt to combine several techniques in two algorithms: coarse grained algorithm and multi thread tournament algorithm. The results obtained from two algorithms are compared, using an algorithm evaluation function. Considering execution time, the coarse grained algorithm performed twice better than the multi thread algorithm.


genetic algorithm; parallel computing; scheduling problem

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ISSN 2088-8708, e-ISSN 2722-2578