• Journal of the Korea Society for Simulation
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• v.10 no.1
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• pp.1-12
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• 2001

This article describes the application of discrete event simulation in a process industry (coffee manufacturing) as a daily production-scheduling tool. A large number of end products (around 300), sporadic demand, and limited shelf life of coffee (90 days) make it difficult to generate feasible production schedules manually. To solve this problem, an integrated system was developed incorporating discrete event simulation methodology into scheduling process. The integrated system is comprised of two components: a scheduling program and a simulation model. The scheduling program is used to generate daily schedules for roasting, grinding, and packing coffee. The simulation model uses the generated schedules to simulate the production of coffee and regenerates a modified production schedule. In this paper, each of the components will be described in detail, evaluated in terms of performance factors, and validated with a set of real production data. Although this article focuses on a specific system, we will share our experiences and Intuitions gained and encourage other process industries to develop simulation-based scheduling tools.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.432-434
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• 2008

전력거래소에서는 수요관리에 대한 지원금을 수요측의 입찰제도를 통하여 결정하는 시범사업을 실시하고 있다. 본 논문은 수요입찰에 의한 지원금의 결정에 관여하는 급전계획 프로그램에 대한 내용을 기술하고 있다. Scheduling 프로그램은 수요의 비선형 특성을 고려하기 위하여 혼합정수계획법(MIP)을 이용하여 작성하였으며 효용성을 입증하기 위한 사례검토를 수행하였다.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.1
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• pp.98-106
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• 1996

An irrigation scheduling model, IRIS developed to evaluate irrigation demand and irrigation time for upland crops. For IRlS modeling the soil moisture simulation model, SWATRER was adopted and modified. The developed model, IRIS operated under 5 different soil moisture level that is 20%, 40%, 60%, 80% of available soil moisture and optimum soil moisture level, OSML, which is different about the growing stage and no rainfall condition during growing period. As a result for IRIS simulation, irrigation demand for 5 different soil moisture level was 332.3, 409.8, 569.3, 732.2, 539.3mm, irrigation number was 5, 8, 18, 54, 16 times and irrigation interval during peak time of consumptive use was 20, 13, 6, 2, 6 days respectively. It is appeared that the higher soil moisture level the more irrigation demand and irrigation number and the higher soil moisture level the less irrigation interval.

• IE interfaces
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• v.11 no.2
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• pp.13-24
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• 1998

A distribution system is composed of multiple levels from a producer to customers, and it's objective is to supply customers with goods timely with a prescribed level of quality at a minimum cost. For the installation and operation of multi-echelon distribution system, DRP(Distribution Resource Planning) is widely used. However, because of the characteristic difference of material flow dynamic of each distribution center, it is almost impossible to get the optimal distribution scheduling. In this paper, an improved DRP method to schedule multi-echelon distribution network is proposed so that the lot-size and order point is dynamically obtained to meet the change of demand rate and timing. The experiment is done with various demand pattern, forecast errors of demand and lead times of central distribution center. The proposed method is compared with traditional statistical approach.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2406-2412
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• 2015

Multi-user multi-input multi-output (MU-MIMO) system has attracted the 4^th generation wireless network as one of core technique for performance enrichment. In this system rate control is a challenging problem and another problem is optimization. Proper scheduling can resolve these problems by deciding which set of user and at which rate the users send their data. This paper proposes a new multi-parameter based scheduling (MPS) for downlink multi-user multiple-input multiple-output (MU-MIMO) system under space-time block coding (STBC) transmissions. Goal of this MPS scheme is to offer improved link level performance in terms of a low average bit error rate (BER), high packet delivery ratio (PDR) with improved resource utilization and service fairness among the user. This scheme allows the set of users to send data based on their channel quality and their demand rates. Simulation compares the MPS performance with other scheduling scheme such as fair scheduling (FS), normalized priority scheduling (NPS) and threshold based fair scheduling (TFS). The results obtained prove that MPS has significant improvement in average BER performance with improved resource utilization and fairness as compared to the other scheduling scheme.

• International Journal of Contents
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• v.8 no.4
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• Journal of the military operations research society of Korea
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• v.29 no.1
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• pp.112-119
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• 2003

The procedure and implementation of an simulation based production planning and scheduling system. Production planning and scheduling is important problem in manufacturing field. It is so important for delivery quality as well as productivity, too. In this paper, heuristic production planning and scheduling module for improving delivery quality and productivity will be discussed. Beginning with total demand and initial work in process, the algorithms for production scheduling and planning can efficiently generate a feasible production resources and capacity schedule results in high resource utilization, minimum number of the late orders and reduced labor variability. The algorithm is executed to achieve the best on time delivery performance. The developed heuristic algorithms in the module will be expected to provide the better delivery performance and productivity.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.28-33
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• 2000

This article describes the application of discrete event simulation in a process industry (coffee manufacturing) as a daily production-scheduling tool. A large number of end products (around 300), sporadic demand, and limited shelf life of coffee (90 days) make it difficult to generate feasible production schedules manually. To solve this problem an integrated system was developed incorporating discrete event simulation methodology into scheduling process. The integrated system is comprised of two components: a scheduling program and a simulation model. The scheduling program is used to generate daily schedules for roasting, grinding, and packing coffee. The simulation model uses the generated schedules to simulate the production of coffee and regenerates a modified production schedule. In this paper, each of the components will be described in detail, evaluated in terms of performance factors, and validated with a set of real production data. Although this article focuses on a specific system, we will share our experiences and intuitions gained and encourage other process industries to develop simulation-based scheduling tools.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.701-703
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• 1996

Maintenance scheduling plays an important role in evaluating the supply reliability of power systems. Since generating units must be maintained and inspected, the generation planner must schedule planned outages during the year. Several factors entering into this scheduling analysis include: seasonal load-demand profile, amount of maintenance to bo done on all generating units, size of the units, elapsed time from last maintenance, and availability of maintenance crews. This paper proposes a new algorithm to decide the multi-year maintenance scheduling with considering the total cost. We adjust the maintenance scheduling to levelize the reliability over all period. The proposed algorithm is applied to a real size power system and the developed reliability results are obtained.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1097-1102
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• 2011

This paper proposes the registration information, the participation information for classifying demand resources participate in demand response program. Modeling demand resources from them, it evaluates values of demand resources. Specially assuming that ignore the loss in power system, they take a role as generation. This paper proposes how to evaluate demand resources' values. Case study shows that demand response operators schedule efficiently demand response program by using index of such as the registration information the participation information of demand resource.