An Impact of Cross Over Operator on the Performance of Genetic Algorithm Under Operating System Process Scheduling Problem

The following research paper describe the use of genetic algorithm for operating system process scheduling problem. The scheduling problem is consider as NP hard problem. Genetic algorithm is consider as meta heuristic optimization tool. The main aim of genetic algorithm is to adapt itself according to the problem under consideration. The power of genetic algorithm is depends upon its operators such as crossover, mutation, inversion, reproduction etc. crossover operator has exploitive property. In this paper we use different type of cross over operator with constant crossover and mutation probability. The convergence state, adaptability and performance of genetic algorithm is varying according to the crossover and mutation operator used.