This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i.e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduli...

Currently, job schedulers require “rigid” job submissions from users, who must specify a particular number of processors for each parallel job. Most parallel jobs can be run on different processor partition sizes, but there is often a trade-off between wait-time and run-time — asking for many processors reduces run-time but may require a protracted wait. With moldable scheduling, the choice of ...

Grid computing is a form of distributed computing that involves coordinating and sharing data storage and network resource. The goal of grid job scheduling is to achieve high system throughput and match the job to the appropriate available computing resource. The complexity of scheduling problem increases with heterogeneous nature of grid and is highly difficult to schedule effectively. Existin...

In hadoop, the job scheduling is an independent module, users can design their own job scheduler based on their actual application requirements, thereby meet their specific business needs. Currently, hadoop has three schedulers: FIFO, computing capacity scheduling and fair scheduling policy, all of them are take task allocation strategy that considerate data locality simply. They neither suppor...

Dynamic scheduling algorithms are gaining more and more special attention for their satisfying robustness when confronted with unexpected events as well as their considerably high performance in scheduling. An organization structure for intelligent job shop scheduling based on MAS (Multiple Agents System) is put forward to achieve effective and efficient production. A hybrid multilayer agent st...

The job-shop scheduling problem has attracted many researchers’ attention in the past few decades, and many algorithms based on heuristic algorithms, genetic algorithms, and particle swarm optimization algorithms have been presented to solve it, respectively. Unfortunately, their results have not been satisfied at all yet. In this paper, a new hybrid swarm intelligence algorithm consists of par...

The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the propos...

Flexible work schedules give nurses the freedom and control to manage the demands of work and home, allow organisations to meet their staffing needs and can improve job satisfaction. This article reports the results of an integrative review of published peer-reviewed research and personal narratives that examined nurses' perceptions of the relationship between job satisfaction and a self-schedu...

This paper uses trace-driven simulation to study the unfairness properties of Web server scheduling strategies, such as Processor Sharing (PS) and Shortest Remaining Processing Time (SRPT). We use a general-purpose probe-based sampling approach to estimate the mean and variance of the job response time for different job sizes, for arbitrary arrival processes and service time distributions. The ...

Meeting due dates is the most important goal of scheduling if the due date of each job has been promised to its customer. This paper considers the job-shop scheduling problem of minimizing the total holding cost of completed and in-process products subject to no tardy jobs. A heuristic algorithm based on the shifting bottleneck procedure is proposed for solving the minimum total holding cost pr...