• 한국통신학회논문지
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• 제33권3C호
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• pp.219-233
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• 2008

스케줄링의 목적은 입력 작업(DAG)에 대한 스케줄 결과 길이를 최소화하는 것이다. 이런 스케줄링 문제는 잘 알려진 '정해진 시간 내에 해결하기 어려운 문제(NP-complete)'이며 최적의 스케줄링 결과 값을 얻기 위해서는 휴리스틱으로 해결해야 한다. 선후 관계의 제약을 갖는 노드들의 스케줄링을 효율적으로 수행하기 위해 부모 노드와 이질 프로세서에 대한 정보를 고려하는 TANH(the Task duplication based scheduling Algorithm for Network of Heterogeneous systems), GDL, BIL, TDS과 같은 많은 알고리즘이 제안되었다. 본 논문은 기존의 TANH 스케줄링에서 나타나는 여러 개의 부모 노드와 이질 프로세서에 대한 다양한 경우를 충분히 고려하지 못한 점을 보안하여 향상된 스케줄링을 수행할 수 있는 DTSC (Duplication based Task Scheduling with Communication Cost in Heterogeneous Systems)알고리즘을 제안하였다. 제안된 알고리즘의 성능은 기존 TANH, GDL 알고리즘과 비교하였으며, 스케줄링의 성능 향상을 보여 주었다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.109-113
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• 2002

Steel industry is the most capital intensive and the largest energy consuming industry, which operate huge and complex facilities to supply various steel products as the primary materials to almost every manufacturing industry Major steel products are hot-rolled and cold-rolled coils, plates, and wires that are produced through molten iron making, molten steel making, casting, and rolling. Each process runs in batch between setups and the specifications or bach are different with each other High energy consuming and heavy material handling require careful synchronization or processes, as well. Considering the synchronization or processes, the lot planning and scheduling problem in the integrated steelmaking process rovers the roll grouping with given casts. the sequencing or rolls over time, and the machine assignment and time scheduling or charges and casts. The problem is investigated by dividing it into two cases whether single or parallel machines at the molten steel making and the continuous casting processes. Problem descriptions and solution approaches or each instance are introduced. To test their performance and conformity, implementation or the algorithms and numerical experiments are carried out with real world and constructed data sets.

• 대한산업공학회지
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• 제36권2호
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• pp.125-137
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• 2010

This study focuses on the problem of scheduling wafer lots of several product families in the deposition workstation in a semiconductor wafer fabrication facility. There are multiple identical parallel machines in the deposition workstation, and two types of setups, record-dependent setup and family setup, may be required at the deposition machines. A record-dependent setup is needed to find optimal operational conditions for a wafer lot on a machine, and a family setup is needed between processings of different families. We suggest two-phase heuristic algorithms in which a priority-rule-based scheduling algorithm is used to generate an initial schedule in the first phase and the schedule is improved in the second phase. Results of computational tests on randomly generated test problems show that the suggested algorithms outperform a scheduling method used in a real manufacturing system in terms of the sum of weighted flowtimes of the wafer lots.

• 대한산업공학회지
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• 제30권2호
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• pp.107-119
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• 2004

A study on the following parallel machine problem is addressed in this research. An order is completed only when a given number of processes (cycle) are repeated. Anew cycle is possible only upon the completion of the previous cycle. Orders are classified into job group according to product feature. For a machine to switch to a different job group from the currently processing one a major setup is required while a minor setup time is inserted in between two jobs of the same job group. The objective of the study is to find a schedule that minimizes total weighted tardiness. An initial solution is obtained by the RATCS(Restricted Apparent Tardiness Cost with Setup) rule, and a Tabu search is applied to improve the solution. Numerical examples are also presented.

• 한국경영과학회지
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• 제17권1호
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• pp.41-41
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• 1992

In the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.

• 산업경영시스템학회지
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• 제36권4호
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• pp.116-122
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• 2013

This study develops a dynamic scheduling model for parallel machine scheduling problem based on genetic algorithm (GA). GA combined with discrete event simulation to minimize the makespan and verifies the effectiveness of the developed model. This research consists of two stages. In the first stage, work sequence will be generated using GA, and the second stage developed work schedule applied to a real work area to verify that it could be executed in real work environment and remove the overlapping work, which causes bottleneck and long lead time. If not, go back to the first stage and develop another schedule until satisfied. Small size problem was experimented and suggested a reasonable schedule within limited resources. As a result of this research, work efficiency is increased, cycle time is decreased, and due date is satisfied within existed resources.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제9권9호
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• pp.189-196
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• 2020

최근 클라우드 환경에서는 고성능 연산이 가능한 GPU(Graphics Processing Unit) 장치를 가상머신에게 적용한 GPU 클라우드 컴퓨팅 기술이 많이 사용되고 있다. 클라우드 환경에서 가상머신에게 할당된 GPU 장치는 대규모 병렬 처리를 통해 CPU보다 더 빠르게 연산을 수행할 수 있으며, 이로 인해 다양한 분야의 고성능 컴퓨팅 서비스들을 클라우드 환경에서 운용할 때 많은 이점을 얻을 수 있다. 클라우드 환경에서 GPU 장치는 가상머신의 성능 향상에 많은 도움을 주지만 가상머신의 CPU 사용 시간을 기반으로 작동하는 가상머신 스케줄러에서는 GPU 장치의 사용 시간이 고려되지 않아 다른 가상머신들의 성능에 영향을 미친다. 본 논문에서는 클라우드 환경에서 가상머신에게 GPU를 할당할 때 많이 사용되는 직접 통로기반 GPU 가상화 환경에서 GPGPU(General-Purpose computing on Graphics Processing Units) 작업을 수행하는 가상머신으로 인한 다른 가상머신들의 성능 저하 현상을 검증하고 분석하며, 이를 해결하기 위한 가상머신의 GPGPU 작업 관리 기법을 제안한다.