• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.672-677
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• 2016

Development of Internet has been successfully inspired with extensive deployment of the network technology and application. However, increases in Internet usage had caused a lot of traffic overload in these days. Thus, we need a continuous research and development on the network virtualization for effective resource allocation. In this paper, we propose a minimal cost virtual network mapping algorithm using Piecewise Linear Cost Function. We exploited an algorithm with Linear Programming and D-VINE for node mapping, and Shortest Path Algorithm based on linear programming solution is used for link mapping. In this way, we compared and analyzed the average cost for arrival rate of VN request with linear and tree structure. Simulation results show that the average cost of our algorithm shows better efficiency than ViNEyard.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1506-1509
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• 1999

This paper presents a new economic dispatch algorithm to improve the unit commitment solution while guaranteeing the near optimal solution without reducing calculation speed. The conventional economic dispatch algorithms have the problem that it is not applicable to the unit commitment formulation due to the frequent on/off state changes of units during the unit commitment calculation. Therefore, piecewise linear iterative method have generally been used for economic dispatch algorithm for unit commitment. In that method, the approximation of the generator cost function makes it hard to obtain the optimal economic dispatch solution. In this case, the solution can be improved by introducing a inverse of the incremental cost function. The proposed method is tested with sample system. The results are compared with the conventional piecewise linear iterative method. It is shown that the proposed algorithm yields more accurate and economical solution without calculation speed reduction.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.141-150
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• 2011

Precise image-to-image registration is required to process multi-sensor data together. The purpose of this paper is to develop an algorithm that register between high-resolution optical and SAR images using linear features. As a pre-processing step, initial alignment was fulfilled using manually selected tie points to remove any dislocations caused by scale difference, rotation, and translation of images. Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on their similarity. Outliers having larger geometric differences than general matching points were eliminated. The remaining points were used to construct a new transformation model, which was combined the piecewise linear function with the global affine transformation, and applied to increase the accuracy of geometric correction.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.353-359
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• 2009

This paper proposes a novel technique for calculating the security costs that properly includes ramping constraints in the operation of a deregulated power system. The ramping process is modeled by a piecewise linear function with certain assumptions. During this process, a ramping cost is incurred if the permissible limits are exceeded. The optimal production costs of the power producers are calculated with the ramping cost included, considering a time horizon with N-1 contingency cases using contingency constrained optimal power flow (CCOPF), which is solved by the primal-dual interior point method (PDIPM). A contingency analysis is also performed taking into account the severity index of transmission line outages and its sensitivity analysis. The results from an illustrative case study based on the IEEE 30-bus system are analyzed. One attractive feature of the proposed approach is that an optimal solution is more realistic than the conventional approach because it satisfies physical constraints, such as the ramping constraint.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.57-64
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• 1989

An Economic selection of specification limits is considered for a given target value in a complete inspection plan. Each item is inspected, and if it meets the specification, it is accepted. Items less than the lower specification limit are scrapped or sold at a reduced price, and those greater than the upper specification limit are reworked. Cost factors to be considered are economic loss caused by quality deviations, rework cost and scrapping cost. Methods for finding the optimal specification limits are given for the cases of piecewise linear loss function and quadratic loss function with illustrative examples.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.8
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• pp.374-379
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• 2000

The nodal marginal cost and the congestion charge are used as the econimic signals for the electricity price and new invetments in deregulated power systems. In this paper, the nodal marginal cost and the congestion charge are calculated by using the shadow prices resulted from the calculation of Optimal Power Flow(OPF). Linearization of inequality constraints and piecewise linear cost functions make an OPF problem LP-based forms. In order to use the shadow price, the Interior Point(IP) algorithm is applied as a solution technique to the formulation. This paper proposes an algorithm to determine efficients initial points which are guaranteed to be interior points.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.943-949
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• 2005

An economic design of specification limits for production process of ham is considered for a given process mean in a complete inspection plan. Each ham is inspected, and if it meets the specification, it is accepted. The ham less than the lower specification limit are changed another products or at a discounted price, and those greater than the upper specification limit are reworked. A profit model is developed which involves selling price, production cost, rework cost and the cost which is incurred by imperfect quality. Methods for finding the optimal specification limits are derived for the case of piecewise linear loss function with an industrial case study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.26-36
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• 2021

The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.

• Korean Management Science Review
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• v.10 no.1
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• pp.193-205
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• 1993

This paper presents a mathematical model for a class of vertical integration decisions. The problem structure of interest consists of raw material vendors, components suppliers, components processing plants, final product (assembly) plants and external components buyers. Economic feasibility of operating components plants instead of keeping outside suppliers is our major concern. The model also determines assignment of product lines and production volumes to each open plant considering the cost impacts of economies of scale and plant complexity. The problem formulation leads to a concave, mixed integer mathematical program. Given the state of the art of nonlinear programming techniques, it is often not possible to find global optima for reasonably sized such problems. We developed an optimization solution algorithm within the framework of Benders decomposition for the case of a piecewise linear concave cost function. It is shown that our algorithm generates optimal solutions efficiently.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.5
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• pp.75-82
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• 2002

This paper propose a new mathematical modelling method about optimum operational schedule for cogeneration systems. Proposed algorithm solving the energy product cost function in this paper is very similar to the real model that is, proposed algorithm solve nonlinear type of real model using mixed integer programming based on the piecewise linear function while the conventional algorithms used before could not solve that kind of problems. The effectiveness of the proposed method is ascertained by the simulation results with varius case studies which are similar to real operation circumstances.