In the last decade job shop scheduling problems have been subject to intensive research due to their multiple applications. Job shop scheduling is known as a strongly NPcomplete problem. In the job shop scheduling problems, processing times and due dates are very dynamically due to both human and machine resource factors. Fuzzy sets are used to model the uncertain processing times and due dates...

The existing resource and topology heterogeneity has divided the scheduling solutions into local schedulers and high-level schedulers (a.k.a. meta-schedulers). Although much work has been proposed to optimise job queue based scheduling, seldom has attention been put on the job sharing behaviours between decentralised distributed resource pools, which in turn raises a notable opportunity to expl...

In this paper, we analyze the characteristics of the job shop scheduling problem. A new genetic algorithm for solving the agile job shop scheduling is presented to solve the job shop scheduling problem. Initial population is generated randomly. Two-row chromosome structure is adopted based on working procedure and machine distribution. The relevant crossover and mutation operation is also desig...

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this paper is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load w...

We introduce the multiple capacitated job shop scheduling problem as a generalization of the job shop scheduling problem. In this problem machines may process several operations simultaneously. We present an algorithm based on constraint satisfaction techniques to handle the problem e ectively. The most important novel feature of our algorithm is the consistency checking. An empirical performan...

Scheduling of jobs is a challenging problem in grid. Efficient job scheduling is essential for the effective utilization of the resources. We propose a grid model as a collection of clusters. In this paper, we apply Divisible Load Theory (DLT) and Least Cost Method (LCM) to model the grid scheduling problem involving multiple worker nodes in each cluster. We propose a hybrid job scheduling algo...

Fairness is an important issue for parallel job scheduling policies, but has been ignored in most of previous studies. In this paper, we consider two different styles of job fairness: FCFS and EQ. Commonly used summary statistics are applied to different job measures to evaluate the fairness under a wide range of non-preemptive parallel job scheduling policies, including priority backfill polic...

This paper examines load sharing and job scheduling in a network of workstations (NOW). Along with traditional methods of load sharing and job scheduling, it also examines methods referred to as epoch load sharing and epoch scheduling respectively. Epoch load sharing evenly distributes the load among workstations with job migration that occurs only at the end of predefined intervals. The time i...

In this paper a novel scheduling model based on resource contention called the interference paradigm is presented. Using this paradigm, a range of scheduling policy options can be expressed. A simulation study of several interference-based scheduling policies in a NOW environment suggests that this approach can produce reduced completion time and high job throughput for a sequential and paralle...

In this paper we will analyze the performance of job scheduler based on many parameters considering the criticality of job. Many job scheduling algorithms have been devised which affect the performance of the system in their own way. Improvement in job scheduling strategies will play a pivotal role in increasing the overall performance of the system. In this work we discuss some basic job sched...