  Tasks scheduling is the most challenging problem in the parallel computing.
Hence, the inappropriate scheduling will reduce or even abort the utilization
of the true potential of the parallelization. Genetic algorithm (GA) has been
successfully applied to solve the scheduling problem. The fitness evaluation is
the most time consuming GA operation for the CPU time, which affect the GA
performance. The proposed synchronous master-slave algorithm outperforms the
sequential algorithm in case of complex and high number of generations problem.
