• Title/Summary/Keyword: Batch Scheduling

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Economic Scheduling of Multiple Feedstock Biogas Production Systems on Two Identical Digesters (두 개의 동일한 소화조로 이루어진 메탄가스 생산체제의 경제적 운영에 관한 연구)

  • Gim, Bong-Jin
    • Journal of the Korean Operations Research and Management Science Society
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    • v.15 no.1
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    • pp.37-46
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    • 1990
  • Biomass to methane production is a good supply of substitutable energy resources. The economic viability of these systems depends a great deal on cost effective production methods and facilities. The operational problem is to determine the time eto allocate to each batch of several feedstocks for each digester and to determine the number of batches for each digester so as to maximize biogas production for two identical digesters over a fixed planning horizon. This paper provides an efficient approximation procedure which is based on decomposition of the problem and the analysis of incremental gas production function for each feedstock. The computational experience for the heuristic procedure was also reported.

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Incompatible Batch Scheduling with Setup Time (공정 교체 시간을 고려한 배치작업의 일정관리)

  • 김주일;이영훈
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.04a
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    • pp.103-106
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    • 2000
  • 본 논문은 작업이 공정시간 등의 특성으로 인해 Family 로 구분되어지고 동일한 Family 내의 작업끼리만 배치로 구성할 수 있는 제조환경에서의 스케줄링에 관한 연구이다. 이때 배치의 최대크기는 정해져 있어 그 이하의 수로 구성된 작업들로 하나의 배치를 구성할 수 있다. 동일 Family 내의 작업은 작업시간이 동일하고 배치로 구성된 작업이 진행될 때 수에 관계없이 하나의 작업에 소요되는 시간과 동일한 시간이 소요된다. 또한 다른 Family 와의 작업이 이어질 때는 교제시간이 발생한다. 목적함수는 전체지연 시간을 최소화하는 것이며 납기는 동일한 Family 에 있는 작업일지라도 각 작업별로 주어진다. 이 목적함수의 최적해를 구할 수 있는 동적계획법을 제시하고 이를 응용한 발견적 기법을 개발, 적용하여 각각 성능비교를 실시하였다.

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An Empirical Performance Analysis on Hadoop via Optimizing the Network Heartbeat Period

  • Lee, Jaehwan;Choi, June;Roh, Hongchan;Shin, Ji Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5252-5268
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    • 2018
  • To support a large-scale Hadoop cluster, Hadoop heartbeat messages are designed to deliver the significant messages, including task scheduling and completion messages, via piggybacking to reduce the number of messages received by the NameNode. Although Hadoop is designed and optimized for high-throughput computing via batch processing, the real-time processing of large amounts of data in Hadoop is increasingly important. This paper evaluates Hadoop's performance and costs when the heartbeat period is controlled to support latency sensitive applications. Through an empirical study based on Hadoop 2.0 (YARN) architecture, we improve Hadoop's I/O performance as well as application performance by up to 13 percent compared to the default configuration. We offer a guideline that predicts the performance, costs and limitations of the total system by controlling the heartbeat period using simple equations. We show that Hive performance can be improved by tuning Hadoop's heartbeat periods through extensive experiments.

An Adaptive Workflow Scheduling Scheme Based on an Estimated Data Processing Rate for Next Generation Sequencing in Cloud Computing

  • Kim, Byungsang;Youn, Chan-Hyun;Park, Yong-Sung;Lee, Yonggyu;Choi, Wan
    • Journal of Information Processing Systems
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    • v.8 no.4
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    • pp.555-566
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    • 2012
  • The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

Stability Analysis of a Networked Control System with Multiple Packet Transmission (다중 패킷을 전송하는 네트워크 제어시스템의 안정성 분석)

  • Jung, Joon-Hong;Park, Ki-Heon;Lee, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.5
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    • pp.18-29
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    • 2007
  • The main objective of this paper is to propose a new stability analysis method for a networked control system with multiple packet transmission. The new scheduling method that can guarantee the maximum time delay and discrete switch state equation model which represent a network data loss is proposed. The equivalent model of a MIMO(multi-input multi-output) networked control system is derived from a state space model of linear time invariant interconnected systems in the form of asynchronous dynamical system. Using this model, this paper presents new stability theorems that can determine stability of the networked control system with regard to time delay, data loss, and the number of transmission packets. Simulation results verify the effectiveness of proposed stability analysis method.

A Case Study on Lead Time Improvement Using a Simulation Approach (시뮬레이션 방식을 이용한 리드 타임 개선 사례 연구)

  • Ro, Wonju;Sim, Jaehun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.2
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    • pp.140-152
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    • 2021
  • During the shift from gasoline vehicles to electric ones, auto parts manufacturing companies have realized the importance of improvement in the manufacturing process that does not require any layout changes nor extra investments, while maintaining their current production rate. Due to these reasons, for the auto part manufacturing company, I-company, this study has developed the simulation model of the PUSH system to conduct a process analysis in terms of production rate, WIP level, and logistics work's utilization rate. In addition, this study compares the PUSH system with other three manufacturing systems -KANBAN, DBR, and CONWIP- to compare the performance of these production systems, while satisfying the company's target production rate. With respect to lead-time, the simulation results show that the improvement of 77.90% for the KANBAN system, 40.39% for the CONWIP system, and 69.81% for the DBR system compared to the PUSH system. In addition, with respect to WIP level, the experimental results demonstrate that the improvement of 77.91% for the KANBAN system, 40.41% for the CONWIP system, and 69.82% for the DBR system compared to the PUSH system. Since the KANBAN system has the largest impacts on the reduction of the lead-time and WIP level compared to other production systems, this study recommends the KANBAN system as the proper manufacturing system of the target company. This study also shows that the proper size of moving units is four and the priority allocation of bottleneck process methods improves the target company's WIP and lead-time. Based on the results of this study, the adoption of the KANBAN system will significantly improve the production process of the target company in terms of lead-time and WIP level.