• 제목/요약/키워드: Scheduling Optimization

검색결과 452건 처리시간 0.023초

Markov State Model을 이용한 복합화력 발전설비의 최적의 유지보수계획 수립 (Application Markov State Model for the RCM of Combustion Turbine Generating Unit)

  • 이승혁;신준석;김진오
    • 전기학회논문지
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    • 제56권2호
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    • pp.248-253
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    • 2007
  • Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

뉴럴 네트워크와 시뮬레이티드 어닐링법을 하이브리드 탐색 형식으로 이용한 어패럴 패턴 자동배치 프로그램에 관한 연구 (Study on Hybrid Search Method Using Neural Network and Simulated Annealing Algorithm for Apparel Pattern Layout Design)

  • 장승호
    • 한국생산제조학회지
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    • 제24권1호
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    • pp.63-68
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    • 2015
  • Pattern layout design is very important to the automation of apparel industry. Until now, the genetic algorithm and Tabu search method have been applied to layout design automation. With the genetic algorithm and Tabu search method, the obtained values are not always consistent depending on the initial conditions, number of iterations, and scheduling. In addition, the selection of various parameters for these methods is not easy. This paper presents a hybrid search method that uses a neural network and simulated annealing to solve these problems. The layout of pattern elements was optimized to verify the potential application of the suggested method to apparel pattern layout design.

Multiple Product Single Facility Stockout Avoidance Problem (SAP) and Weighted Stockout Problem (WSP)

  • Moon, Il-Kyeong
    • 한국경영과학회지
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    • 제17권3호
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    • pp.137-158
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    • 1992
  • We study the Multiple Product Single Facility Stockout Avoidance Problem (SAP). That is the problem of determining, given initial inventories, whether there is a multiple product single facility production schedule that avoids stockouts over a given time horizon. The optimization version of the SAP where stockouts are pnelized linearly is also studied. We call this problem the Weighted Stockout Problem (WSP). Both problems are NP-hard in the strong sense. We develop Mixed Integer Linear Programming (MIP) formulations for both the SAP and the WSP. In addition, several heuristic algorithms are presented and performances are tested using computational experiments. We show that there exist polynomial algorithms for some special cases of the SAP and the WSP. We also present a method to phase into a target cyclic schedule for infinite horizon problems. These can be used as a practical scheduling tool for temporarily overloaded facilities or to reschedule production after a disruption.

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마코프 누적 프로세스에서의 확률적 콘벡스성 (Stochastic convexity in markov additive processes)

  • 윤복식
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1991년도 춘계공동학술대회 발표논문 및 초록집; 전북대학교, 전주; 26-27 Apr. 1991
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    • pp.147-159
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    • 1991
  • Stochastic convexity(concvity) of a stochastic process is a very useful concept for various stochastic optimization problems. In this study we first establish stochastic convexity of a certain class of Markov additive processes through the probabilistic construction based on the sample path approach. A Markov additive process is obtained by integrating a functional of the underlying Markov process with respect to time, and its stochastic convexity can be utilized to provide efficient methods for optimal design or for optimal operation schedule of a wide range of stochastic systems. We also clarify the conditions for stochatic monotonicity of the Markov process, which is required for stochatic convexity of the Markov additive process. This result shows that stochastic convexity can be used for the analysis of probabilistic models based on birth and death processes, which have very wide application area. Finally we demonstrate the validity and usefulness of the theoretical results by developing efficient methods for the optimal replacement scheduling based on the stochastic convexity property.

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클러스터 컴퓨팅 환경에서 자원 스케줄링의 최적화 (An Optimization of Resource Scheduling in the Cluster Computing Environment)

  • 이훈순;김창수
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2016년도 추계학술발표대회
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    • pp.56-57
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    • 2016
  • 본 논문에서는 클러스터 컴퓨팅 환경에서 가용한 자원의 추이를 고려한 자원 스케줄링 최적화 방법을 제안한다. 제안하는 스케줄링 방법은 데이터 인텐시브 응용의 특성인 자원 추가에 따른 처리 성능의 선형적 확장성을 활용하는데, 사용자가 작업 수행을 위해 명시한 자원이 가용하지 않은 경우에 해당 자원이 가용해질 때까지 기다리는 것이 아니라 가용한 자원 상황 추이를 고려하여 융통성 있는 자원 할당을 하게 함으로써 자원 조각화를 최소화한다. 시물레이션을 통한 실험으로 제안하는 방법이 기존 방법에 비해 자원 활용률과 처리량 측면에서 우수함을 검증하였다.

Proportional Fair Scheduling Algorithm in OFDMA-Based Wireless Systems with QoS Constraints

  • Girici, Tolga;Zhu, Chenxi;Agre, Jonathan R.;Ephremides, Anthony
    • Journal of Communications and Networks
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    • 제12권1호
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    • pp.30-42
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    • 2010
  • In this work we consider the problem of downlink resource allocation for proportional fairness of long term received rates of data users and quality of service for real time sessions in an OFDMA-based wireless system. The base station allocates available power and subchannels to individual users based on long term average received rates, quality of service (QoS) based rate constraints and channel conditions. We formulate and solve a joint bandwidth and power optimization problem, solving which provides a performance improvement with respect to existing resource allocation algorithms. We propose schemes for flat as well as frequency selective fading cases. Numerical evaluation results show that the proposed method provides better QoS to voice and video sessions while providing more and fair rates to data users in comparison with existing schemes.

Cost-Aware Dynamic Resource Allocation in Distributed Computing Infrastructures

  • Ricciardi, Gianni M.;Hwang, Soon-Wook
    • International Journal of Contents
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    • 제7권2호
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    • pp.1-5
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    • 2011
  • Allocation of computing resources is a crucial issue when dealing with a huge number of tasks to be completed according to a given deadline and cost constraints. The task scheduling to several resources (e.g. grid, cloud or a supercomputer) with different characteristics is not trivial, especially if a trade-off in terms of time and cost is considered. We propose an allocation approach able to fulfill the given requirements about time and cost through the use of optimizing techniques and an adaptive behavior. Simulated productions of tasks have been run in order to evaluate the characteristics of the proposed approach.

직렬 생산라인에 대한 DBR 방식의 평가 (Evaluation of DBR system in a serial production line)

  • 고시근
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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    • pp.470-475
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    • 2002
  • An alternative to traditional production planning and control systems such as MRP and JIT is the drum-buffer-rope (DBR). Using the DBR system, companies can achieve a large reduction of work-in-process (WIP) and finished-goods inventories (FGI). significant improvement in scheduling performance, and substantial earnings increase. The purpose of this paper is to analyze the effect of the DBR system in a serial production line. Using Markov process, we modeled a DBR system with three stages. For the model developed we analyze the system characteristics and then present an optimization model for system design. The system performance is also analyzed through sensitivity analysis.

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마코프 누적 프로세스에서의 확률적 콘벡스성과 그 응용 (Stochastic convexity in Markov additive processes and its applications)

  • 윤복식
    • 한국경영과학회지
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    • 제16권1호
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    • pp.76-88
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    • 1991
  • Stochastic convexity (concavity) of a stochastic process is a very useful concept for various stochastic optimization problems. In this study we first establish stochastic convexity of a certain class of Markov additive processes through probabilistic construction based on the sample path approach. A Markov additive process is abtained by integrating a functional of the underlying Markov process with respect to time, and its stochastic convexity can be utilized to provide efficient methods for optimal design or optimal operation schedule wide range of stochastic systems. We also clarify the conditions for stochastic monotonicity of the Markov process. From the result it is shown that stachstic convexity can be used for the analysis of probabilitic models based on birth and death processes, which have very wide applications area. Finally we demonstrate the validity and usefulness of the theoretical results by developing efficient methods for the optimal replacement scheduling based on the stochastic convexity property.

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크로스도킹 시스템 하에서의 최적 트럭 일정계획 수립에 따른 제품 손상의 최소화에 대한 연구 (Minimizing Product Damage through Optimal Truck Schedule in a Cross Docking System)

  • 유우연
    • 대한안전경영과학회지
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    • 제7권1호
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    • pp.137-146
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    • 2005
  • 크로스도킹은 물류센터의 운영 개념으로써 입고트럭에 의해 배달된 물품이 재고로써 보관됨이 없이 즉시 고객의 수요에 따라 재분류되어 출고트럭에 적재되어 고객에게 배달되는 프로세스로 구성된다. 본 연구에서는 임시보관 장소를 보유한 크로스도킹 시스템의 총 운영시간을 최소화하기 위한 입고 트럭과 출고 트럭의 일정계획 수립을 위한 수학적 모델을 개발하였다. 본 연구에서 개발한 모델의 적용으로 물류센터 내에서의 자재 취급 빈도 및 시간이 감소하여 제품 손상을 최소화 시키는 효과가 기대된다.