• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.14-23
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• 1996

Scheduling jobs effectively under consideration of actual loads on machines is one of the most complicated tasks in production control. The complexity of the finite capacity scheduling often makes the conventional methods of industrial engineering fail. As an alternative, Knowledge-based approaches to job-shop scheduling have been evolved recently. This paper presents a blackboard- based scheduling expert system which combines knowledge-based scheduling with interactive scheduling. It is shown to be possible to generate the feasible schedule within a reasonable time. Flexible reaction management is also possible while keeping the changes in the generated schedule to the minimal and adjusting the schedule to tardy operations or working environmental changes. The system is equipped with a rule base with heuristics for handling conflicted event. A case study applying the implemented system is described.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.165-170
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• 2023

Scheduling algorithms plays a significant role in optimizing the CPU in operating system. Each scheduling algorithms schedules the processes in the ready queue with its own algorithm design and its properties. In this paper, the performance analysis of First come First serve scheduling, Non preemptive scheduling, Preemptive scheduling, Shortest Job scheduling and Round Robin algorithm has been discussed with an example and the results has been analyzed with the performance parameters such as minimum waiting time, minimum turnaround time and Response time.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.1-12
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• 1992

Parallel Genetic Algorithms (GAs) are developed to solve a single machine n-job scheduling problem which is to minimize the sum of absolute deviations of completion times from a common due date. (0, 1) binary scheme is employed to represent the n-job schedule. Two selection methods, best individual selection and simple selection are examined. The effect of crossover operator, due date adjustment mutation and due date adjustment reordering are discussed. The performance of the parallel genetic algorithm is illustrated with some example problems.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.71-77
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• 2013

In the information flooded situation having many thing to do, the efficient scheduling of energy and time is regarded as a very important thing for the busy modern people. Because the efficient time scheduling already became a very important key factor for a successful life, the more elaborately designed intelligent system than the previous simple event oriented scheduling system should be supported. Accordingly in this paper we propose Classified Job Scheduling System in which jobs are classified by Time value & Importance and allocated to Time frame efficiently. Especially the new method is proposed with the policy that processes the job with high time value first and concurrently allocates the job of low time vale & high importance to the preempted fixed area of time frame for continuous processing of job which has a key of success in the future.

• Management Science and Financial Engineering
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• v.11 no.2
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• pp.19-43
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• 2005

This paper considers a variation of the customer order scheduling problem, and the variation is the case where the machine-job assignment is fixed. We examine the parallel machine environment, and the objective is to minimize the sum of the completion times of the batches. While a machine can process only one job at a time, different machines can simultaneously process different jobs in a batch. The recognition version of this problem is known to be NP-complete in the strong sense even if there exist only two parallel machines. When there are an arbitrary number of parallel machines, we establish three lower bounds and develop a dynamic programming (DP) algorithm which runs in exponential time on the number of batches. We present two simple but intuitive heuristics, SB and GR, and find some special cases where SB and GR generate an optimal schedule. We also find worst case upper bounds on the relative error. For the case of the two parallel machines, we show that GR generates an optimal schedule when processing times of all batches are equal. Finally, the heuristics and the lower bounds are empirically evaluated.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.31-37
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• 2006

To achieve the efficient performance within a mobile grid considering the intermittent network connectivity and non-dedicated heterogeneous mobile devices, this paper suggests the scheduling algorithm of job allocation as a viable solution. The suggested scheduling algorithm has two core functions, the prediction of response time for task processing and the identification of the optimal number of mobile devices to process the mobile grid applications. This scheduling algorithm suggests the numerical formulas to calculate the network latency considering the effects of heterogeneous non-dedicated mobile system in wireless network environments. Also we evaluate the performance of mobile grid system using the processing the distributed applications in implemented mobile grid environments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.101-109
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• 2008

This paper considers an integrated decision for scheduling and outsourcing(or, subcontracting) of a finite number of jobs(or, orders) in a time-sensitive make-to-order manufacturing environment. The jobs can be either processed in a parallel in-house facilities or outsourced to subcontractors. We should determine which jobs should be processed in-house and which jobs should be outsourced. And, we should determine the schedule for the jobs to be processed in-house. If a job is determined to be processed in-house, then the scheduling cost(the completion time of the Job) is imposed. Otherwise(if the job should be outsourced), then an additional outsourcing cost is imposed. The objective is to minimize the linear combination of scheduling and outsourcing costs under a budget constraint for the total available outsourcing cost. In the problem analysis, we first characterize some solution properties and then derive dynamic programming and branch-and- bound algorithms. An efficient heuristic is also developed. The performances of the proposed algorithms are evaluated through various numerical experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.39-60
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• 2017

In the Cloud, for the scheduling of parallel jobs, there are many tasks in a job and those tasks are executed concurrently on different VMs (Visual machines), where each task of the job will be executed synchronously. The goal of scheduling is to reduce the execution time and to keep the fairness between jobs to prevent some jobs from waiting more time than others. We propose a Cloud model which has multiple Clouds, and under this model, jobs are in different lists according to the waiting time of the jobs and every job has different parallelism. At the same time, a new method-ZOMT (the scheduling parallel tasks based on ZERO-ONE scheduling with multiple targets) is proposed to solve the problem of scheduling parallel jobs in the Cloud. Simulations of ZOMT, AFCFS (Adapted First Come First Served), LJFS (Largest Job First Served) and Fair are executed to test the performance of those methods. Metrics about the waiting time, and response time are used to test the performance of ZOMT. The simulation results have shown that ZOMT not only reduces waiting time and response time, but also provides fairness to jobs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.1-9
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• 2010

In this paper, we consider a two-machine re-entrant permutation flowshop scheduling problem with the objective of minimizing total flowtime, and suggest branch and bound algorithms for the scheduling problem. In this scheduling problem, each job must be processed twice on each machine, that is, each job should be processed on the two machines in the order of machine 1, machine 2 and then machine 1 and machine 2. In this research, based on the results of existing researches for re-entrant permutation flowshop scheduling problems, various dominance properties, lower bound and heuristic algorithm are suggested for the problem, and those are used to develop branch and bound algorithms. In the computational experiments for evaluation of the performance of the algorithms, the suggested branch and bound algorithms are tested on randomly generated test problems and results are reported.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.2
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• pp.209-229
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• 1996

Scheduling problems which determine the sequence of jobs are one of the Important issues to many industries. This paper deals with a single-machine job sequencing problem which has complex constraints and an objective function. To solve the problem, an expressive constraint description language and an automatic code generator are developed for our scheduling system. The user just needs to describe the scheduling problem using the constraint description language that allows to express both quantitative and qualitative constraints as well as an objective function in real world semantics. Then, a complete scheduling program based on constraint satisfaction technique is automatically generated through the code generator. Advantage of this approach is that models of the scheduling problems are easily developed and maintained because models ore formulated by using the language which reflects real world semantics.