A flow shop scheduling problem involves scheduling jobs on multiple machines in series in order to optimize a given criterion. The flow time of a job is the amount of time the job spent before its completion and the stretch of the job is the ratio of its flow time to its processing time. In this paper, a hybrid genetic algorithm (HGA) approach is proposed for minimizing the total stretch in flo...

This paper presents a new simulation methodology for scheduling and coordinating decentralized job shops using multi-computer systems. The parallel working subsystems of an integrated production system are distributed across a network of computers. Utilizing the special structure of parallel processor architectures new coordination and scheduling rules for job shops are designed and evaluated. ...

Grid computing aggregates heterogeneous resources for executing resource intensive applications of science and engineering. Grid scheduling is a complex problem (NP-hard) to map existing tasks to accessible storage and computational resources to utilize them in the optimistic manner. In this article, we have analyzed the grid scheduling problem, the process of job scheduling, challenges and app...

In this work, we present slot selection algorithms for job batch scheduling in distributed computing with non-dedicated resources. Jobs are parallel applications and these applications are independent. Existing approaches towards resource co-allocation and parallel job scheduling in economic models of distributed computing are based on search of time-slots in resource occupancy schedules. The s...

In this paper we study the performance of parallel job scheduling in a distributed system. A special type of scheduling called gang scheduling is considered. In gang scheduling jobs consist of a number of interacting tasks, which are scheduled to run simultaneously on distinct processors. Two gang scheduling policies are used to schedule parallel jobs for two different types of job parallelism....

We provide several non-approximability results for deterministic scheduling problems whose objective is to minimize the total job completion time. Unless P = NP, none of the problems under consideration can be approximated in polynomial time within arbitrarily good precision. Most of our results are derived by Max SNP hardness proofs. Among the investigated problems are: scheduling unrelated ma...

We describe a scheduling technique in which estimated job runtimes and estimated resource availability are used to efficiently distribute workloads across a homogeneous grid of resources with variable availability. The objective is to increase efficiency by minimizing job failure caused by resources becoming unavailable. Optimal scheduling will be accomplished by mapping jobs onto resources wit...

This paper investigates single-machine scheduling problems with piece-rate machine maintenance and interval constrained actual processing time. The actual processing time of a job is a general function of the normal job processing time and the position in job sequence, and it is required to restrict in given interval otherwise earliness or tardiness penalty should be paid. The maintenance durat...

The n-job, m-machine flow shop scheduling problem is one of the most general job scheduling problems. This study deals with the multi objective optimization with the criteria of makespan minimization and minimization of total weighted flow time for the flow shop scheduling problem. The n-job mmachine problem is known to be NP hard problem, several meta heuristics have been applied so far in the...

In this paper we present a linear time approximation scheme for the job shop scheduling problem with fixed number of machines and fixed number of operations per job. This improves on the previously best 2 + ǫ, ǫ > 0, approximation algorithm for the problem by Shmoys, Stein, and Wein. Our approximation scheme is very general and it can be extended to the case of job shop scheduling problems with...