• Journal of Korean Society on Water Environment
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• v.23 no.3
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• pp.356-366
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• 2007

In this paper a methodology is developed to prioritize replacement of water distribution pipes according to the economical efficiency of replacement and assess the long-term effects of water main replacement policies on water distribution systems. The methodology is implemented with MATLAB to develop a computer algorithm which is used to apply the methodology to a case study water distribution system. A pipe break prediction model is used to estimate future costs of pipe repair and replacement, and the economically optimal replacement time of a pipe is estimated by obtaining the time at which the present worth of the total costs of repair and replacement is minimum. The equation for estimating the present worth of the total cost is modified to reflect the fact that a pipe can be replaced in between of failure events. The results of the analyses show that about 9.5% of the pipes in the case study system is required to be replaced within the planning horizon. Analyses of the yearly pipe replacement requirements for the case study system are provided along with the compositions of the replacement. The effects of water main replacement policies, for which yearly replacement length scenario and yearly replacement budget scenario are used, during a planning horizon are simulated in terms of the predicted number of pipe failures and the saved repair costs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.37-52
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• 1998

In many distribution systems important cost reductions and/or service improvements may be achieved by adopting an efficient inventory policy and proper selection of facilities. These efficiency improvements and service enhancements clearly require an integrated approach towards various logistical planning functions. The areas of inventory control and transportation planning need to be closely coordinated. The purpose of this paper is to construct an integrated model that can minimize the total cost of the transportation and inventory systems between multiple origin and destination points, where in origin point i has the supply of commodities and in destination point j requires the commodities. In this case, demands of the destination points are assumed random variables which have a known probability distribution. Using the lot-size reorder-point policy and the safety stock level that minimize total cost we find optimal distribution centers which transport the commodities to the destination points and suggest an optimal inventory policy to the selected distribution center. We also show if a demand greater than one unit will occur at a particular time, we describe the approximate optional replenishment policy from computational results of this lot-size reorder-point policy. This model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and a computer program with UNIX C language. In the usefulness review, we show the meaning and validity of the proposed model and exhibit the results of a comparison between our approach and the traditional approach, respectively.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.171-177
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• 2021

In terms of distribution planning, accurate electric load prediction is one of the most important factors. The future load prediction has manually been performed by calculating the maximum electric load considering loads transfer/switching and multiplying it with the load increase rate. In here, the risk of human error is inherent and thus an automated maximum electric load forecasting system is required. Although there are many existing methods and techniques to predict future electric loads, such as regression analysis, many of them have limitations in reflecting the nonlinear characteristics of the electric load and the complexity due to Photovoltaics (PVs), Electric Vehicles (EVs), and etc. This study, therefore, proposes a method of predicting future electric loads on distribution lines by using Machine Learning (ML) method that can reflect the characteristics of these nonlinearities. In addition, predictive models were developed based on actual data collected at KEPCO's existing distribution lines and the adequacy of developed models was verified as well. Also, as the distribution planning has a direct bearing on the investment, and amount of investment has a direct bearing on the maximum electric load, various baseline such as maximum, lowest, median value that can assesses the adequacy and accuracy of proposed ML based electric load prediction methods were suggested.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.9-19
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• 1993

We present a production planning and control system suitable for small to medium sized, order-based companies producing special gases of small-quantity. The proposed system uses cards each of which represents individual unit of order. The components and procedure of the system are described in detail. The proposed system is easy to implement because it visualizes the amount and distribution of the received orders; and requires minimum aid of computer.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.22-35
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• 1999

The block assembly process takes more than half of the total shipbuilding processes. Therefore, it is very important to have a practically useful block assembly process planning system which can build plans of maximum efficiency with minimum man-hours required. However, the process plans are often not readily executable in the assembly shops due to severe imbalance of workloads. This problem arises because the process planning is done on block by block basis in current practice without paying any attention to the load distribution among the assembly shops. this paper presents the development of an automated hull block assembly process planning system which results in the most effective use of production resources and also produces plans that enable efficient time management. If the load balance of assembly shops is to be considered at the time of process planning, the task becomes complicated because of the increased computational complexity. To solve this problem, a new approach is adopted in this research in which the load balancing function and process planning function are iterated alternately providing to each other contexts for subsequent improvement. The result of case study with the data supplied from the shipyard shows that the system developed in this research is very effective and useful.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1744-1753
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• 2016

The main purpose of this article is a complex hyperthermia applicator system design for treatment of head and neck region. The applicator system is composed of four waveguides with a stripline horn aperture and circular water bolus. The specific absorption rate (SAR) and temperature distribution from this applicator in various numerical phantom models was investigated. For used targets, the treatment planning based on the optimization process made through the SEMCAD X software is added to show the steering possibilities of SAR and thereby temperature distribution. Using treatment planning software, we proved that the SAR and temperature distribution can be effectively controlled (by amplitude and phase changing) improving the SAR and temperature target coverage approximately by 20 %. For the proposed applicator system analysis and quantitative evaluation of two parameters 25 % iso-SAR and $41^{\circ}C$ iso-temperature contours in the treatment area with the respect to sensitive structures in treatment area were defined. To verify our simulation results, the real measurement of reflectivity coefficient as well as the temperature distribution in a homogenous phantom were performed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.19-27
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• 2008

This paper addresses determining the location of the distribution centers in a discrete dynamic distribution system. In discrete and finite time horizon, the demands of retailers are dynamic for the periods. Some locations among the retailers can be chosen for the role of the distribution centers at the beginning of each period. The distribution centers have to be located at the location of minimizing logistics cost. Logistics cost factors are the operation cost and the fixed cost of distribution center, and the transportation cost. The distribution centers of minimizing sum of operation cost, fixed cost and transportation cost are determined among retailers in each period for the planning period. A mathematical model was formulated and a dynamic programming based algorithm was developed. A numerical example was shown to explain our problem.

• Journal of the Korea Safety Management & Science
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• v.11 no.4
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• pp.193-199
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• 2009

Recently, an industrial production-distribution planning problem has been widely investigated in Supply Chain Management(SCM). One of the key issues in the current SCM research area is reverse logistics network. This study have developed a simulation model for the reverse logistics network. The simulation model analysis reverse logistics network issues such as inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment. Computational experiments using commercial simulation tool ARENA show that the real problems. The model can be used to decide an appropriate production-distribution planning problem in the research area.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.9-15
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• 2005

In the operation of distribution systems, DGs (Distributed Generations) are installed as an alternative to extension and the establishment of substations, transmission and distribution lines according to the increasing power demand. In the operation planning of DGs, determining optimal capacity and allocation achieves economical profitability and improves the reliability of power distribution systems. This paper proposes a determining method for the optimal number, size and allocation of DGs in order to minimize the operation costs of distribution systems. Capacity and allocation of DGs for economical operation planning duration are determined to minimize total cost composed with power buying cost, operation cost of DGs, loss cost and outage cost using the GA (Genetic Algorithm).

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.69-73
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• 1978

This paper deals with the problem of determining the optimal inventory-transportation policy of the idealistically simple inventory-transportation system with the following assumptions: (1) The system consists of a single central warehouse and a single local warehouse, (2) The planning horizon is finite, (3) Demand rate is fixed costant, and so forth. Developed is the algorithm by which to identify the optimal inventory policy which minimizes the total cost incurred to the system over the given finite planning horizon. A sample numerical example is presented along with a discussion of the possible applications of the approach used n the algorithm.