• Environmental and Resource Economics Review
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• v.32 no.3
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• pp.149-166
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• 2023

The emissions trading system, introduced to reduce greenhouse gas emissions, experienced a sharp increase in emission allowance prices during the second plan period (2018-2020), which led to an increase in the demand for smooth supply and demand of emission allowances, while suppliers anticipating a shortage of emission allowances in the future did not participate in trading. Therefore, the authority temporarily revised the guidelines to ensure that the amount of allowances carried forward is proportional to the trading volume as a market stabilization measure. Through an optimization process using a dynamic nonlinear mathematical model, this paper analyzes the impact of the government's intervention on the carryover policy on GHG emission reductions and emission allowance market prices. According to the simulation analysis results, banking regulations could cause a decline in prices during the regulation period, even though the initial policy was predicted to be adopted.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.131-142
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• 1991

The concept of criterion function is proposed as a framework for comparing the geometric and computational characteristics of various nonlinear programming approaches to linear programming such as the method of centers, Karmakar's algorithm and the gravitational method. Also, we discuss various computational issues involved in obtaining an efficient parallel implementation of these methods. Clearly, the most time consuming part in solving a linear programming problem is the direction finding procedure, where we obtain an improving direction. In most cases, finding an improving direction is equivalent to solving a simple optimization problem defined at the current feasible solution. Again, this simple optimization problem can be seen as a least squares problem, and the computational effort in solving the least squares problem is, in fact, same as the effort as in solving a system of linear equations. Hence, getting a solution to a system of linear equations fast is very important in solving a linear programming problem efficiently. For solving system of linear equations on parallel computing machines, an iterative method seems more adequate than direct methods. Therefore, we propose one possible strategy for getting an efficient parallel implementation of an iterative method for solving a system of equations and present the summary of computational experiment performed on transputer based parallel computing board installed on IBM PC.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.143-152
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• 2005

Optimal methods for designing multiplierless IIR filters with cascaded prefilter-equalizer structures are proposed for narrowband applications. Assuming that an U filter consists of a cyclotomic Polynomial (CP) prefilter and an all-Pole equalizer based on interpolated first order polynomial (IFOP), in the proposed method the prefilter and equalizer are simultaneously designed using mixed integer linear programming (MILP). The resulting filter is a cascaded filter with minimal complexity. In addition, MtP tries to minimize both computational complexity and phase response non-linearity. Design examples demonstrate that the proposed methods produce a more efficient cascaded prefilter-equalizer than existing methods.

• Computational Structural Engineering
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• v.9 no.2
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• pp.93-101
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• 1996

An artificial neural network is a computational model that mimics the biological system of the brain and it consists of a number of interconnected processing units where it can reasonably infer by them. Because the neural network is particularly useful for evaluating systems with a multitude of nonlinear variables, it can be used in experimental results predictions, in structural planning and in optimum design of structures. This paper describes the basic theory related to the neural networks and discusses the applicability of neural networks to predict the ultimate shear capacity of the precast concrete vertical joints by comparing the neural networks with a conventional method such as regression.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.163-175
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• 1997

This paper presents the algorithm for finding the compensatory solution for fuzzy multiobjective nonlinear programming problem using $\gamma$-operator. The proposed algorithm can be applied to all cases with multiobjective problems since the interactive process with a decision maker is simple, various uncertainties involved on decision making are eliminated and all the objectives are well balanced. On the basis of proposed algorithm, an illustrative numerical example is presented.

• 전기의세계
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• v.26 no.1
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• pp.77-81
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• 1977

This paper aims to develope a new algorithm to overcome the disadvantages of the conventional E.L.D system based on the B-Constants and Penalty-Factors scheme. The main features of this paper are that the Variabiable Decoupled Method usually employed in the Load-Flow studies is introduced to the E.L.D. algorithm developed by Sasson, using the Powell's Nonlinear Programming Scheme. Besides this, other minor refinements are made to reduce memory spaces and computing time. Case studies show that the method suggested here has the remarkable advantages of computing efficiency and memory requirements over Sasson's.

• Proceedings of the KSR Conference
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• 2001.05a
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• pp.72-79
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• 2001

In this paper we present a nonlinear programming model for the solution of the train seat capacity distribution problem (TSCDP) with a numerical example. The TSCDP model finds the optimal capacity distribution methods which minimize the sum of the differences between the demands and the seat capacities. Also the TSCDP provides the information on the degree of the discrepancy between the demand and the seat capacities. One can use the TSCDP model as a tool for planning train seat capacity planning.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.307-321
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• 1997

In this paper, we consider the expert's ambiguity and the decision maker's fuzzy goals which are incorporated into multiobjective nonlinear programming problems in order to find a compensatory solution. The proposed method can be applied to all cases of multiobjective problems with fuzzy parameters since the interactive process with a decision maker is simple, various uncertainties involved in decision making are eliminated and all the objectives are well balanced. An illustrative numerical example for nonlinear programming problems with fuzzy parameters is demonstrated along with the corresponding computer output.

• Journal of the Korean Society for Railway
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• v.5 no.2
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• pp.77-83
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• 2002

In this paper we present a nonlinear programming model for the train seat capacity distribution with a numerical example. The model finds the optimal capacity distribution methods which minimize the sum of the differences between the demands and the seat capacities. Also the model provides the information on the degree of the discrepancy between the demand and the seat capacities. One can use the model as a tool for planning train seat capacity planning.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.75-80
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• 1996

Fuzzy approaches used to solve MONLP(Multiobjective Nonlinear Programming Problem) are based on the max-min method of fuzzy sets theory However, since the min operator noncompensatory, these approaches can not guarentee an efficient solution to the problem. In this paper, we presents an algorithm for finding the aggregation operator to find efficient solution. In particular, our presented algorithm is guarentee an efficient solution. On the basis of proposed algorithm, an illustrative numerical example is presented.