Enhanced Simulated Annealing Tecniques for Multiprocessor Scheduling

George E. Nasr and A. Harb, Lebanese American University; G. Meghabghab, Valdosta State University

The problem of multiprocessor scheduling can be stated as scheduling a general task graph on a multiprocessor system such that a set of performance criteria will be optimized. This study investigates the use of near optimal scheduling strategies in multiprocessor scheduling problem. The multiprocessor scheduling problem is modeled and simulated using five different simulated annealing algorithms and a genetic algorithm. In this paper, the comparison of the simulation results of the simulated annealing algorithm, the modified versions of simulated annealing algorithms, and the genetic algorithm is presented. In addition, results of sensitivity analysis on the simulated annealing algorithm, the modified simulated annealing algorithms, and the genetic algorithm are included.


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