K. V. Deeba

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Job Scheduling in a Multiprocessor architecture is an extremely difficult NP hard problem, because it requires a large combinatorial search space and also precedence constraints between the processes. For the effective utilization of multiprocessor system, efficient assignment and scheduling of jobs is more important. This paper proposes a new improved(More)
Efficient multiprocessor scheduling is essentially the problem of allocating a set of computational jobs to a set of processors to minimize the overall execution time. The main issue is how jobs are partitioned in which total finishing time and waiting time is minimized. Minimization of these two criteria simultaneously, is a multi objective optimization(More)
Job Scheduling in a M ultiprocessor architecture is an extremely difficult NP hard problem, because it requires a large combinatorial search space and also precedence constraints between the processes. For the effective utilization of multiprocessor system, efficient assignment and scheduling of jobs is more important. This paper proposes a n ew improved(More)
  • K Thanushkodi Director, K Deeba
  • 2012
Many heuristic-based approaches have been applied to finding schedules that minimize the execution time of computing tasks on parallel processors. Particle Swarm Optimization is currently employed in several optimization and search problems due its ease and ability to find solutions successfully. A variant of PSO, called as Improved PSO has been developed(More)
  • K Thanushkodi Director, K Deeba
  • 2011
Particle Swarm Optimization is currently employed in several optimization and search problems due its ease and ability to find solutions successfully. A variant of PSO, called as Improved PSO has been developed in this paper and is hybridized with the simulated annealing approach to achieve better solutions. The hybrid technique has been employed, inorder(More)
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