tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. hence, integration has been proposed to decide about these problems concurrently. main problem in integration is how we can relate pro...

The IT organizations invests heavy capital by consuming large scale infrastructure and advanced operating platforms. The advances in technology has resulted in emergence of cloud computing, which is promising technology to achieve the aforementioned objective. At the peak hours, the jobs arriving to the cloud system are normally high demanding efficient execution and dispatch. An observation th...

This paper presents a predictable and grouped genetic algorithm (PGGA) for job scheduling. The novelty of the PGGA is twofold: (1) a job workload estimation algorithm is designed to estimate a job workload based on its historical execution records, (2) the divisible load theory (DLT) is applied to predict an optimal solution in searching a large scheduling space so...

This paper presents a new algorithm based on integrating Genetic Algorithms and Tabu Search methods to solve the Job Shop Scheduling problem. The idea of the proposed algorithm is derived from Genetic Algorithms. Most of the scheduling problems require either exponential time or space to generate an optimal answer. Job Shop scheduling (JSS) is the general scheduling problem and it is a NP-compl...

supported on many production systems. However, fair share has been shown to cause performance problems for some users, especially the users with difficult jobs. This work is focusing on extending goal-oriented parallel computer job scheduling policies to cover the fair share objective. Goal-oriented parallel computer job scheduling policies have been shown to achieve good scheduling performance...

Grid computing enables sharing, selection and aggregation of computing resources for solving complex and large-scale scientific problems. The resources making up a grid need to be managed to provide a good quality of service. Grid scheduling is a vital component of a Computational Grid infrastructure. This paper presents a dynamic cluster based job scheduling algorithm for efficient execution o...

Processor allocation and job scheduling are two complementary techniques for improving the performance of multiprocessors. It has been observed that all the hypercube allocation policies with the FCFS scheduling provide only incremental performance improvement. A greater impact on the performance can be obtained by eecient job scheduling. This paper presents an eeort in that direction by introd...

This paper describes the radiotherapy patient scheduling problem of minimising waiting times. Like many other service industry problems, radiotherapy patient scheduling may be solved by first modelling and formulating it into a shop scheduling problem. Over the years, these shop scheduling models have been researched and solved using various approaches. This paper typifies radiotherapy patient ...

This paper addresses performance issues associated with job scheduling in a partitionable parallel system. Jobs consist of parallel tasks scheduled to execute concurrently on processor partitions, where each task starts at the same time and computes at the same pace. The performance of different scheduling schemes is compared over various workloads. Various performance metrics are examined. The...

The task of designing and optimizing job scheduling algorithms for heterogeneous computing environments requires the ability to predict scheduling performance. The complexity of heterogeneous scheduling issues requires that the experiments devised to test a scheduling paradigm be both flexible and extensive. Experimentally determined models for the prediction of job execution times on both sequ...