• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.729-731
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• 2004

This paper deals with the design of a low order $H_{\infty}$ controller by using an iterative linear matrix inequality (LMI) method. The low order $H_{\infty}$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the effectiveness of the proposed algorithm.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.951-959
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• 2011

The proposed method is based on a penalized censored regression model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log likelihood function of censored regression model. It provide the efficient computation of regression parameters including variable selection and leads to the generalized cross validation function for the model selection. Numerical results are then presented to indicate the performance of the proposed method.

• Journal of applied mathematics & informatics
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• 제30권5_6호
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• pp.759-772
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• 2012

In this paper, semi-infinite constrained programming, a class of constrained nonsmooth optimization problems, are transformed into unconstrained nonsmooth convex programs under the help of exact penalty function. The unconstrained objective function which owns the primal-dual gradient structure has connection with $\mathcal{VU}$-space decomposition. Then a $\mathcal{VU}$-space decomposition method can be applied for solving this unconstrained programs. Finally, the superlinear convergence algorithm is proved under certain assumption.

• 대한건축학회논문집:구조계
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• 제35권10호
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• pp.135-142
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• 2019

Ant colony optimization(ACO) technique is utilized in truss size optimization with frequency constraints. Total weight of truss to be minimized is considered as the objective function and multiple natural frequencies are adopted as constraints. The modified traveling salesman problem(TSP) is adopted and total length of the TSP tour is interpreted as the weight of the structure. The present ACO-based design optimization procedure uses discrete design variables and the penalty function is introduced to enforce design constraints during optimization process. Three numerical examples are carried out to verify the capability of ACO in truss optimization with frequency constraints. From numerical results, the present ACO is a very effective way of finding optimum design of truss structures in free vibration. Finally, we provide the present numerical results as future reference solutions.

• 한국정밀공학회지
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• 제13권11호
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• pp.73-81
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• 1996

This paper presents a general procedure for the selection of the machining parameters for a given machine which provides the maximum material removal rate using a Genetic Algorithms(GAs). Some constraints were given in order to achieve desired surface integrity and cutting tool life conditions as wel as to protect machine tool. Such a constrained problem can be transformaed to unconstrained problem by associating a penalty with all constraint violations and the penalties are included in the function evaluation. Genetic Algorithms can be used for finding global optimum cutting conditions with respect to the above cost function transformed by pennalty function method. From the demonstration of the numerical results, it was found that the near optimal conditions could be obtained regardless of complex solution space such as cutting environment.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.306-317
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• 2021

The unbalance between system ergodic sum rate and high fairness is one of the key issues affecting the performance of non-orthogonal multiple access (NOMA) system. To solve the problem, this paper proposes a power allocation algorithm to realize the ergodic sum rate maximization of NOMA system. The scheme is mainly achieved by the construction algorithm of fair model based on α fair utility function and the optimal solution algorithm based on the interior point method of penalty function. Aiming at the construction of fair model, the fair target is added to the traditional power allocation model to set the reasonable target function. Simultaneously, the problem of ergodic sum rate and fairness in power allocation is weighed by adjusting the value of α. Aiming at the optimal solution algorithm, the interior point method of penalty function is used to transform the fair objective function with unequal constraints into the unconstrained problem in the feasible domain. Then the optimal solution of the original constrained optimization problem is gradually approximated within the feasible domain. The simulation results show that, compared with NOMA and time division multiple address (TDMA) schemes, the proposed method has larger ergodic sum rate and lower Fairness Index (FI) values.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2001년도 추계학술대회 논문집(Proceeding of the KOSME 2001 Autumn Annual Meeting)
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• pp.3-7
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• 2001

Although elbows are commonly used in practice, many questions regarding the optimum arrangement still remain unanswered. The effect due to an elbow lasts for a considerable distance downstream of the elbow and is severe when two elbows are in the system. The goal of this study is to provide an effective guide for the optimum arrangement of elbows and the optimum design of the approach piping system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.1106-1108
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• 1997

This paper presents a new approach on genetic algorithms to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through combination in penalty function with death penalty, generation-apart elitism, atavism and heuristic crossover. Numerical results on an actual utility system consisted of 13 thermal units show that the proposed approach is faster and robuster than classical genetic algorithm.

• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.89-96
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• 2018

When a fault occurs in a power system, the existing analytic models for the power system fault diagnosis could generate multiple solutions under the condition of one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or an alarm or alarms of these PRs and/or CBs failing. Therefore, this paper presents an improved analytic model addressing the above problem. It takes into account the interaction between the uncertainty involved with PR operation and CB tripping and the uncertainty of the alarm reception, which makes the analytic model more reasonable. In addition, the existing analytic models apply the penalty function method to deal with constraints, which is influenced by the artificial setting of the penalty factor. In order to avoid the penalty factor's effects, this paper transforms constraints into an objective function, and then puts forward an improved immune clonal multi-objective optimization algorithm to solve the optimal solution. Finally, the cases of the power system fault diagnosis are served for demonstrating the feasibility and efficiency of the proposed model and method.

• 한국통신학회논문지
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• 제21권4호
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• pp.1077-1088
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• 1996

In this paper, we propose a new method to analyze the performance degradation by timing jitters in the receivers of intensity modulation/direct detection digital optical communication systems where pulse-shaping filters are used to minimize intersymbol interference. The results obtained from the proposed analytical method show that conventional analytical methods underestimate the influence of timing jitters on the receiver performance. Using the proposed anlaytical method, we derive an analytic equation for approximated power penalty due to timing itters and obtain an exact power penalty by numerical analyses. Assuming Gaussian or uniform probability density function for timing jitters, we also show that assumption of Gaussian distribution for timing jitters yields more performance degration than that of uniform distribution.