An improved genetic algorithm for solving the multiprocessor scheduling problem

Multiprocessor Scheduling Problem (MSP) is an NP-complete optimization problem. The applications of this problem are numerous, but are, as suggested by the name of the problem, most strongly associated with the scheduling of computational tasks in a multiprocessor environment. Many methods and algorithms were suggested to solve this problem due to its importance. Genetic algorithms were among the suggested methods. In this research, sound improvements were done on one of the known papers [3]. Results show very good improvements in increasing the percentage of getting the exact solution as well as decreasing the number of generations needed to converge