• 충청수학회지
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• 제21권4호
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• pp.543-553
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• 2008

This paper is concerned with the optimal control problem of global press for an adsorbate-induced phase transition model. That is, we show the existence of the optimal control and derive the optimality conditions. Moreover, we obtain the uniqueness of the optimal control.

• East Asian mathematical journal
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• 제31권3호
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• pp.371-377
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• 2015

We consider a nondifferentiable robust optimization problem, which has a maximum function of continuously differentiable functions and support functions as its objective function, continuously differentiable functions as its constraint functions. We prove optimality conditions for the nondifferentiable robust optimization problem. We formulate a Wolfe type dual problem for the nondifferentiable robust optimization problem and prove duality theorems.

• East Asian mathematical journal
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• 제31권3호
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• pp.345-349
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• 2015

In this paper, we consider a fractional robust optimization problem (FP) and give necessary optimality theorems for (FP). Establishing a nonfractional optimization problem (NFP) equivalent to (FP), we formulate a Mond-Weir type dual problem for (FP) and prove duality theorems for (FP).

• East Asian mathematical journal
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• 제37권5호
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• pp.543-551
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• 2021

Recently, semidefinite optimization problems have been intensively studied since many optimization problem can be changed into the problems and the the problems are very computationable. In this paper, we consider a semidefinite linear vector optimization problem (VP) and we establish the optimality theorems for (VP), which holds without any constraint qualification.

• 응용통계연구
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• 제20권2호
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• pp.267-280
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• 2007

혼합물 성분들의 비율의 상한과 하한에 대한제한조건이 부과된 제한된 혼합물 실험 공간 R에서의 혼합물 실험을 위한 최적 설계를 찾는 데에 D-, G-, V- 최적기준 등과 같은 다양한 최적 설계 기준이 사용된다. 각각의 실험 설계는 선택된 최적 기준에 대해서는 최적이지만, 제한된 혼합물 실험 공간에서의 예측력에 대해서는 만족스럽지 못하다는 것은 잘 알려진 사실이다. (Vining 등, 1993; Khuri 등, 1999). 우리의 관심사는 2차 혼합물 반응표면모형을 가정한 경우에 제한된 혼합물 공간에서의 효율적인 실험 설계를 찾는 것이다. 이 논문에서는 꼭지점, 선중심점, 면중심점, 중앙점과 내부점으로 구성된 확장된 후보 실험점 그룹을 구성한 다음에, D-최적기준, G-최적기준, V-최적기준과 실험점들 간의 거리에 근거한 U-최적기준에 강건한 실험 설계를 제안한다. Khuri 등(1999)에서 분석된 비료 혼합물 실험과Vining과 Cornell(1993)이 분석한 조명탄 혼합물 실험의 사례에서 강건한 실험설계들과 두 논문에서 추천된 실험 설계들에 대한 예측치의 표준화된 분산의 분위수의 그림(SVPQP)을 비교한 결과 강건한 설계가 상대적으로 우월함이 판명되었다.

• Journal of Ecology and Environment
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• 제31권2호
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• pp.89-95
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• 2008

Sensing the approach of a predator is critical to the survival of prey, especially when the prey has no choice but to escape at a precisely timed moment. Escape behavior has been approached from both proximate and ultimate perspectives. On the proximate level, empirical research about electrophysiological mechanisms for detecting predators has focused on vision, an important modality that helps prey to sense approaching danger. Studies of looming-sensitive neurons in locusts are a good example of how the selective sensitivity of nervous systems towards specific targets, especially approaching objects, has been understood and realistically modeled in software and robotic systems. On the ultimate level, general optimality models have provided an evolutionary framework by considering costs and benefits of visually elicited escape responses. A recent paper showed how neural network models can be used to understand the evolution of visually mediated antipredatory behaviors. We discuss this new trend towards integration of these relatively disparate approaches, the proximate and the ultimate perspectives, for understanding of the evolution of behavior of predators and prey. Focusing on one of the best-studied escape pathway models, the Orthopteran LGMD/DCMD pathway, we discuss how ultimate-level optimality modeling can be integrated with proximate-level studies of escape behaviors in animals.

• Journal of Mechanical Science and Technology
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• 제16권2호
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• pp.203-210
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• 2002

For effective response surface modeling during sequential approximate optimization (SAO), the normalized and the augmented D-optimality criteria are presented. The normalized D-optimality criterion uses the normalized Fisher information matrix by its diagonal terms in order to obtain a balance among the linear-order and higher-order terms. Then, it is augmented to directly include other experimental designs or the pre-sampled designs. This augmentation enables the trust region managed sequential approximate optimization to directly use the pre-sampled designs in the overlapped trust regions in constructing the new response surface models. In order to show the effectiveness of the normalized and the augmented D-optimality criteria, following two comparisons are performed. First, the information surface of the normalized D-optimal design is compared with those of the original D-optimal design. Second, a trust-region managed sequential approximate optimizer having three D-optimal designs is developed and three design problems are solved. These comparisons show that the normalized D-optimal design gives more rotatable designs than the original D-optimal design, and the augmented D-optimal design can reduce the number of analyses by 30% - 40% than the original D-optimal design.

• Management Science and Financial Engineering
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• 제17권2호
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• pp.63-84
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• 2011

The ordinary multiple criteria decision making (MCDM) approach requires two types of input, alternative values and criterion weights, and employs two schemes of alternative prioritization, dominance and potential optimality. This paper allows for incomplete information on both types of input and gives rise to the dominance relationships and potential optimality of alternatives. Unlike the earlier studies, we emphasize that incomplete information frequently takes the form of strict inequalities, such as strict orders and strict bounds, rather than weak inequalities. Then the issues of rising importance include: (1) The standard mathematical programming approach to prioritize alternatives cannot be used directly, because the feasible region for the permissible decision parameters becomes an open set. (2) We show that the earlier methods replacing the strict inequalities with weak ones, by employing a small positive number or zeroes, which closes the feasible set, may cause a serious problem and yield unacceptable prioritization results. Therefore, we address these important issues and develop a useful and simple method, without selecting any small value for the strict preference information. Given strict information on both types of decision parameters, we first construct a nonlinear program, transform it into a linear programming equivalent, and finally solve it via a two-stage method. An application is also demonstrated herein.

• 한국국방경영분석학회지
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• 제8권1호
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• pp.99-107
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• 1982

This paper is concerned with the optimality of exponential smoothing applied to the general IMA process with different moving average and differencing orders. Numerical experiments were performed for IMA(m,n) process with various combinations of m and n, and the corresponding forecast errors were compared. Results show that the higher differencing order is more critical to the optimality of exponential smoothing, i.e., the IMA process with the higher moving average order, forecasted by exponential smoothing, has comparatively smaller forecast error. If the difference between the differencing order and the moving average order becomes larger, the accuracy of forecast by exponential smoothing declines gradually.

• 충청수학회지
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• 제26권4호
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• pp.723-734
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• 2013

A robust optimization problem, which has a maximum function of continuously differentiable functions as its objective function, continuously differentiable functions as its constraint functions and a geometric constraint, is considered. We prove a necessary optimality theorem and a sufficient optimality theorem for the robust optimization problem. We formulate a Wolfe type dual problem for the robust optimization problem, which has a differentiable Lagrangean function, and establish the weak duality theorem and the strong duality theorem which hold between the robust optimization problem and its Wolfe type dual problem. Moreover, saddle point theorems for the robust optimization problem are given under convexity assumptions.