• 자원ㆍ환경경제연구
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• 제15권4호
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• pp.673-692
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• 2006

고갈자원 사용의 동태적 효율성 여부를 검증하기 위해서는 미채굴된 자원의 암묵가격을 추정해야 하는데 기존 연구에서는 자원산업의 한계수입과 한계비용의 차이로 측정하거나 자원채굴량을 준고정시킨 제약비용함수를 추정하여 자원채굴량으로 편미분함으로써 도출하는 방식을 사용하였다. 그러나 이들 방법들은 채굴 투입요소인 자본의 비가단성으로 인하여 일관성이 결여된 추정치가 도출될 개연성, 시장의 독점력에 따라 변하는 한계수입의 가변성 문제와, 불완전한 재화 및 요소시장, 정부규제 등이 존재하는 현실적 상황에서 제약비용함수를 이용할 경우 전제 조건인 생산비용의 최소화가 달성되지 못함으로써 야기될 수 있는 분석결과의 신뢰성 문제 등을 안고 있다. 기존 선행연구의 방법론적 한계점들을 인식하여 본 연구에서는 좀더 일반적이고 현실적 상황에서 고갈자원 사용의 동태적 효율성 여부를 검증할 수 있는 방법을 제시한다. Shephard (1970)의 투입물거리함수를 실증적 모형의 이론적 틀로 활용함으로써 생산요소의 투입량과 최종재화의 산출량에 대한 정보만으로 추정이 가능하고, 생산비용 최소화의 극히 제한적인 상황을 전제하지 않으며, 특히 선형계획기법을 적용함으로써 시계열자료나 합동자료로 회귀 추정할 경우 발생할 수 있는 오차항의 자기상관 문제에 초연할 수 있다. 2%, 5%, 10%, 15%, 20%의 고정 할인율 폭과 실질 이자율의 25%, 50%,100%, 200%, 400%로 산정한 변동할인율을 각각 적용하여 1970년~1993닐 기간 동안 국내 무연탄 채굴의 동태적 효율성 여부를 조사한 결과 고정할인율과 변동할인율 모두에 대해서 국내 무연탄의 세대간 효율적 사용은 이루어지지 않은 것으로 나타났다.

• Journal of applied mathematics & informatics
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• 제27권1_2호
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• pp.149-159
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• 2009

In this paper, we introduce some approximate optimal solutions and an augmented Lagrangian function in nonlinear programming, establish dual function and dual problem based on the augmented Lagrangian function, discuss the relationship between the approximate optimal solutions of augmented Lagrangian problem and that of primal problem, obtain approximate KKT necessary optimality condition of the augmented Lagrangian problem, prove that the approximate stationary points of augmented Lagrangian problem converge to that of the original problem. Our results improve and generalize some known results.

• Communications for Statistical Applications and Methods
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• 제15권2호
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• pp.213-228
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• 2008

Using a linear loss function, this paper considers the one-sided testing problem for the exponential distribution via the empirical Bayes(EB) approach. Based on right censored data, we propose an EB test for the exponential parameter and obtain its convergence rate and asymptotic optimality, firstly, under the condition that the censoring distribution is known and secondly, that it is unknown.

• 대한수학회보
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• 제23권2호
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• pp.141-148
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• 1986

In [1], M. Guignard considered a constraint set in a Banach space, which is similar to that in [2] and gave a first order necessary optimality condition which generalized the Kuhn-Tucker conditions [3]. Sufficiency is proved for objective functions which is either pseudoconcave [5] or quasi-concave [6] where the constraint sets are taken pseudoconvex. In this note, we consider a psedoconvex programming problem in a Hilbert space. Constraint set in a Hillbert space being pseudoconvex and the objective function is restrained by an operator equation. Then we use the methods similar to that in [1] and [6] to obtain a necessary and sufficient optimality condition.

• Nonlinear Functional Analysis and Applications
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• 제27권4호
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• pp.813-837
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• 2022

In this paper we consider inverse problem for a general class of nonlinear stochastic differential equations on Hilbert spaces whose generating operators (drift, diffusion and jump kernels) are unknown. We introduce a class of function spaces and put a suitable topology on such spaces and prove existence of optimal generating operators from these spaces. We present also necessary conditions of optimality including an algorithm and its convergence whereby one can construct the optimal generators (drift, diffusion and jump kernel).

• International Journal of Control, Automation, and Systems
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• 제2권1호
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• pp.15-22
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• 2004

Some recent advances in stability and optimality for the nonlinear receding horizon control (NRHC) or the nonlinear model predictive control (NMPC) are assessed. The NRHCs with terminal conditions are surveyed in terms of a terminal state equality constraint, a terminal cost, and a terminal constraint set. Other NRHCs without terminal conditions are surveyed in terms of a control Lyapunov function (CLF) and cost monotonicity. Additional approaches such as output feedback, fuzzy, and neural network are introduced. This paper excludes the results for linear receding horizon controls and concentrates only on the analytical results of NRHCs, not including applications of NRHCs. Stability and optimality are focused on rather than robustness.

• Journal of applied mathematics & informatics
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• 제26권1_2호
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• pp.75-106
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• 2008

In this paper, we derive necessary optimality conditions for a continuous programming problem in which both objective and constraint functions contain support functions and is, therefore, nondifferentiable. It is shown that under generalized invexity of functionals, Karush-Kuhn-Tucker type optimality conditions for the continuous programming problem are also sufficient. Using these optimality conditions, we construct dual problems of both Wolfe and Mond-Weir types and validate appropriate duality theorems under invexity and generalized invexity. A mixed type dual is also proposed and duality results are validated under generalized invexity. A special case which often occurs in mathematical programming is that in which the support function is the square root of a positive semidefinite quadratic form. Further, it is also pointed out that our results can be considered as dynamic generalizations of those of (static) nonlinear programming with support functions recently incorporated in the literature.

• 한국국방경영분석학회지
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• 제25권2호
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• pp.1-14
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• 1999

Metamodels using response surface methodology (RSM) are used for the optimality analysis of linear programming (LP). They have the form of a simple polynomial, and predict the optimal objective function value of an LP for various levels of the constraints. The metamodelling techniques for optimality analysis of LP can be applied to large-scale LP models. What is needed is some large-scale application of the techniques to verify how accurate they are. In this paper, we plan to use the large scale LP model, strategic transport optimal routing model (STORM). The developed metamodels of the large scale LP can provide some useful information.

• 한국지능시스템학회논문지
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• 제12권1호
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• pp.44-51
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• 2002

본 연구는 선형 생성을 위하여 목적함수로서 fairness 기준을 도입하고 설계변수를 B-spline 곡선의 조정점으로 하며 설계자에 의해서 주어지는 기하학적 제약조건을 만족하도록 하는 최적화를 수행하도록 하였다 본 연구에서는 최적화 방법으로서 GA(Genetic Algorithm)와 최적성 기준(optimality criteria)을 병행하였다.

• 대한조선학회논문집
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• 제39권4호
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• pp.60-65
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• 2002

본 연구는 Form Parameter를 만족하는 선형 생성 과정을 최적화 과정으로 취급하였다. 목적함수는 fairness 기준을 도입하고 설계변수는 B-spline 곡선의 조정점으로 하며 제약조건은 설계자에 의해서 주어지는 기하학적 형상으로 하였다. 최적화 방법은 GA(Genetic Algorithm)와 최적성 기준(optimality criteria)을 병행하였다.