• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.159-167
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• 2009

This paper presents the Improved Pre-prepared Power Demand (IPPD) table and Muller's method as a means of solving the Profit Based Unit Commitment (PBUC) problem. In a deregulated environment, generation companies (GENCOs) schedule their generators to maximize profits rather than to satisfy power demand. The PBUC problem is solved by the proposed approach in two stages. Initially, information concerning committed units is obtained by the IPPD table and then the subprob-lem of Economic Dispatch (ED) is solved using Muller's method. The proposed approach has been tested on a power system with 3 and 10 generating units. Simulation results of the proposed approach have been compared with existing methods and also with traditional unit commitment. It is observed from the simulation results that the proposed algorithm provides maximum profit with less computational time compared to existing methods.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1636-1648
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• 2006

In this paper, we propose a new optimization approach to the rate control problem in a wired-cum-wireless network. A primal-dual interior-point(PDIP) algorithm is used to find the solution of the rate optimization problem. We show a comparison between the dual-based(DB) algorithm and PDIP algorithm for solving the rate control problem in the wired-cum-wireless network. The PDIP algorithm performs much better than the DB algorithm. The PDIP can be considered as an attractive method to solve the rate control problem in network. We also present a numerical example and simulation to illustrate our conclusions.

• The Research Journal of the Costume Culture
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• v.5 no.1
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• pp.71-83
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• 1997

It is the important situation that the fashion industry is faced to enormous changes in the nation and worldwide market. To cope with this situations, it is necessary to clarify that the concept of fashion design and its process. This study was conducted as followings : 1. Fashion design is the process of problem solving including the steps of understanding problem, visualizing the image of a design concept. 2. The systematic and intuitive approach is harmonized to solve the process of fashion design. 3. The step of understanding problem is consist of the analysis of environments, the explanation of problem, the determination of purposes, the definition of problem and the visualizing the image of a design concept. 4. In the step of the visualizing the image of a design concept, the intuitive approaches can be clarifies as the importance of start, the step by step process, the determination of a design concept, the fixations of an image, the image realization through real objects, the diminution a difference between a concept and a visualizing the image and the necessity of exercises.

• Journal of Korean Philosophical Society
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• v.144
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• pp.205-234
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• 2017

In this essay, I modify and improve an anger-solving approach based on Seneca's theory of anger. Seneca proposed his own theory on anger and its therapy in his book, De Ira. Jin-Nam Yi developed five-step-anger-solving approach based on Seneca's theory and John Dewey's problem-solving steps. I show that Yi's approach is restricted in preventive short-term therapy with a constricted concept of anger. I also propose that we should treat controllable anger on preventive levels and uncontrollable anger on therapeutic levels. Adding the sixth step, 'jumping' in order to treat counselees with uncontrollable angers, I suggest a new anger-solving approach with clinical examples.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.21-26
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• 1996

The identification of radioactive source in a medium with a limited number of external detectors is introduced as an inverse radiation transport problem. This kind of inverse problem is usually ill-posed and severely under-determined, however, its applications are very useful in manu fields including medical diagnosis and nondestructive assay of nuclear materials. Therefore, it is desired to develop efficient and robust solution algorithms. As an approach to solving inverse problems, an artificial neural network is proposed. We develop a modified version of the conventional Hopfield neural network and demonstrate its efficiency and robustness.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1142-1149
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• 2003

Various organizational factors effect successful implementation of IT enabled business transformation. Among them, the most critical success factor is deemed to overcoming change management problem. Lots of studies have been made on Implementation methodologies and business process formalizations to encourage organizational members to accept new business process changes. However, the logic or process redesign still depends on qualitative problem solving techniques mostly depending on basically human intuition such as brainstorming. cause-and-effect analysis. and so on. In this paper, we focused on developing analytic framework to design to-be business process structure. which can complement qualitative problem solving procedures. With effective use of IT as an enabler, we provide algorithmic framework applicable to designing various business process changes such as process automation, business process resequencing, and more radical process integration. The framework follows dynamic programming approach in the literature, which is based on the decision making paradigm of organizations to abstract business processes as quantitative decision models. As such, our research ran fill the gap of limited development of theory based analytic methodologies for business process design, by providing objective rationale to reach the consensus among the organizational members including senior management.

• Journal of the Korea Society for Simulation
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• v.12 no.1
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• pp.59-71
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• 2003

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involves reducing both production and distribution costs. The purpose of this study is to determine the optimum quantity of production and transportation with minimum cost in the supply chain network. We have presented a mathematical model that deals with real world factors and constraints. Considering the complexity of solving such model, we have applied the genetic algorithm approach for solving this model using a commercial genetic algorithm based optimizer. The results for computational experiments show that the real size problems we encountered can be solved in reasonable time.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.4
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• pp.180-187
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• 2001

This paper proposes an efficient evolutionary programming algorithm for solving a generation expansion planning(GEP) problem known as a highly-nonlinear dynamic problem. Evolutionary programming(EP) is an optimization algorithm based on the simulated evolution (mutation, competition and selection). In this paper, new algorithm is presented to enhance the efficiency of the EP algorithm for solving the GEP problem. By a domain mapping procedure, yearly cumulative capacity vectors are transformed into one dummy vector, whose change can yield a kind of trend in the cost value. To validate the proposed approach, this algorithm is tested on two cases of expansion planning problems. Simulation results show that the proposed algorithm can provide successful results within a resonable computational time compared with conventional EP and dynamic programming.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.131-145
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• 1995

This paper presents a method for solving project planning problem which the opinions of experts greatly disagree in each activity processing time. Triangular fuzzy numbers (TFNs) are used to represent activity times of experts. And we introduce a pessimistic project planning with major TFNs and an optimistic project planning with minor. TFNs, and illustrate the approach using a combination of the existing composite and the comparison methods, which is used to solve the complex project planning problem.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.388-393
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• 1990

A robot manipulator and an obstacle are described mathematically in joint space, with the mathematical representation for the collision between the robot manipulator and the obstacle. Using these descriptions, the robot motion planning problem is formulated which can be used to avoide a time varying obstacle. To solve the problem, the constraints on motion planning are discretized in joint space. An analytical method is proposed for planning the motion in joint space from a given starting point to the goal point. It is found that solving the inverse kinematics problem is not necessary to get the control input to the joint motion controller for collision avoidance.