A deadline-aware modified genetic algorithm for scheduling jobs with burst time and priorities

Abstract

Scheduling plays a vital role in our real life, same as CPU scheduling majorly affects the performance of computer system. For better performance, scheduling depends upon the parameters of jobs (arrival time, burst time, priority, etc.). Different algorithms have been used to find the above factors. Many algorithms such as FCFS, SJF, round-robin, priority are applied, but all these techniques provide a sequence of jobs relevant to their properties. Developing an appropriate sequence using previously known algorithms takes exponential time. This paper proposes an efficient method for process scheduling using a deadline-aware approximation algorithm, where required schedule has a certain weightage of priority and burst time of job. Here, GA and modified GA are compared in terms of number of iterations, number of test cases, requirement percentage and tardiness (fitness value). The results demonstrate that modified GA approach produces solutions very close to the optimal one in comparison with GA.