Efficient scheduling of tabu search round robin earliest deadline and first come first serve with genetic algorithm

Abstract

The problem of scheduling n jobs on m machines with each job having specific machine route has been researched over the decade. The Job Shop Scheduling (JSS) is one of the hardest combinatorial optimization problems. Each resource can process at most one job at a time. An initial schedule is obtained the Genetic algorithm; the results are given as an input to Tabu Search and Round Robin to improve the status of initial scheduling. The research is mainly focus on to reduce the processing time, waiting time, burst time and turnaround time in number of jobs. This study proposes a new approach to evaluate a Job Shop Scheduling problem with the help of Tabu Search (TS), Round Robin (RR), Earliest Deadline First (EDF) and First Come First Serve (FCFS), Genetic Algorithm with Tabu Search, Round Robin, Earliest Deadline First and First Come First Serve. This approach is a very good result with the help of efficient scheduling. The job scheduling is the process of completing jobs over a time with allocation of shared resources. It is mainly used in proper environment, in which the jobs are allocated to various jobs. The scheduling are used in transportation, services batch system, Distributed Resource Management System (DRMS), Distributed Resource Manager (DRM), workload automation, newline