          !  "  ##"$ %%# &   ’’’( © 2010, IJARCS All Rights Reserved 160 ISSN No. 0976-5697 A Modified Cross Over Genetic Algorithm Approach To Single Processor Scheduling Problem Er.Rajiv Kumar* Assistant Professor Computer Engg.Deptt. N.C.College of Engineering Israna, Panipat Haryana rajiv_kumar_gill1@yahoo.co.in Er Sanjeev Gill Lecturer, Civil Engg. Deptt. Global research Institute of Management & Technology Radaur Yamuna Nagar,Haryana sanjeev_kumar_gill1@yahoo.co.in Er. Ashwani Kaushik Lecturer,Mechanical Engg Deptt. N.C.College of Engineering Israna, Panipat ashwanikrkaushik@rediffmail.com Abstract: There are numerous approach to scheduling problems. Scheduling problem is a NP hard problem. This paper present the modified cross over genetic algorithm approach to single processor process scheduling. Single processor machine efficiency depends upon the efficient scheduling of single processor. The work present in this paper shows that processor scheduling can be optimize by apply efficient scheduling algorithm. Extensive computational experiments are carried out to get optimum efficiency of the proposed algorithm. Efficiency of the scheduling algorithm can be examined on number of factors. In this paper we consider average waiting time, turn around time and weighted turn around time as an optimization criteria of scheduling algorithms. Simulation in this paper evaluates the performance and efficiency of proposed algorithm. Experimental results indicates that MCOGA shoes better results than that of traditional scheduling algorithms. Keywords: MCOGA, Genetic algorithm, NP-hard, CPU, Scheduling,Optimization. I. INTRODUCTION Process scheduling in the single processor system is a critical factor in the overall system efficiency[1]. Process scheduling in a single processor system can be consider as allocation of ready process to processor. Typically scheduling problems are NP Hard [2] problems. There is necessity to find out robust & flexible solution for the real world scheduling problem. Genetic algorithms (GAs) were first proposed by the John Holland[3] in the 1960s. The GA is a heuristic search technique that simulates the processes of natural selection and evolution. Genetic algorithm (GA) is a promising global optimization technique [4]. It works by emulating the natural process of evolution as a means of progressing towards the optimal solution. A genetic algorithm has the capability to find out the optimal job sequence which is to be allocated to the CPU. This paper proposes the genetic algorithm based technique to find out the optimal job sequence. We will examine that whether genetic algorithm based scheduling will maximize the operating system performance. The algorithm starts with a population which is consists of several solution to the optimization problem. A member of population is called an individual. A fitness value is associated with each individual. Each solution in the population or an individual is encoded as a string of symbols. These symbols are known as genes & the solution string is called a chromosome. The values taken by genes are called alleles. Several pair of individual (parents) in the population mate to produce offspring by applying the genetic operator crossover. Selection of parents is done by repeated use of a choice function. A number of individuals & off springs are passed to a new generation such that the number of individual in the new population is the same as old population. A selection function determines which string forms the population in the next generation. Each serving string undergoes inversion with a specified probability. II. PROBLEM DESCRIPTION In order to schedule the process in a Single processor operating system ,Let us suppose that there are N processes ( 1,2,3….N) and these processes have their static burst time .we consider batch process system here. These process has been processed on a single CPU at a time. The aim is to find out optimal processes sequence[5] by which the processes can be schedule[6] by the allocation of CPU in such a way that total average waiting time , turnaround time, weighted turnaround time will be minimum A. Assumption for process scheduling problem 1. There are no. of processes waiting for the allocation of CPU. 2. The processes are independent and compete for the allocation of resources.