• Communications of the Korean Mathematical Society
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• v.30 no.3
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• pp.327-337
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• 2015

This paper is concerned with the optimality conditions for optimal control problem of Belousov-Zhabotinskii reaction model. That is, we obtain the optimality conditions by showing the differentiability of the solution with respect to the control. We also show the uniqueness of the optimal control.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.21-26
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• 2012

Two previous studies that attempted to generalize the deterministic joint pricing-inventory decision model are reevaluated. We prove analytically that even in a single-product environment, the EOQ model with constant priceelastic demand cannot find optimal solutions unless two optimality conditions associated with price elasticity and demand magnitude are satisfied. Due to the inexistence of the general optimality for the problem, demand function and price elasticity must be evaluated and bounded properly to use the methods proposed in the previous studies.

• Speech Sciences
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• v.2
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• pp.109-124
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• 1997

This paper shows how a distinctive feature model can effectively be implemented into speech understanding within the framework of the Optimality Theory(OT); i.e., to show how distinctive features can optimally be extracted from given speech signals, and how segments can be chosen as the optimal ones among plausible candidates. This paper will also show how the sequence of segments can successfully be matched with optimal words in a lexicon.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.31-36
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• 2022

Interval caching is one of the representative caching strategies used in multimedia streaming systems. However, there has been no theoretical analysis on interval caching. In this paper, we present an optimality proof of the interval caching policy. Specifically, we propose a caching performance model for multimedia streaming systems and show the optimality of the interval caching policy based on this model.

• Journal of the Chungcheong Mathematical Society
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• v.21 no.4
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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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.89-96
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• 2005

Numerical procedure of design optimality evaluation is studied for caisson structural systems. Two kinds of evaluation methods can be considered; mathematical optimality criteria method (MOCM) and numerical optimization method (NOM). The choice of the method depends on the available information of the system MOCM can be used only when the information of all function values, gradients and Lagrange multipliers is available, which may not be realistic in practice. Therefore, in this study, NOMs are applied for the structural optimality evaluation, where only design variables are necessary. To this end, Metropolis genetic algorithm (MGA) is advantageously used and applied for a standard optimization model of caisson composite breakwater. In the numerical example, cost and constraint functions are assumed to be changed from the orignal design situation and their effects are evaluated for optimality. From the theoretical consideration and numerical experience, it is found that the proposed optimality evaluation procedure with MGA-based NOM is efficient and practically applicable.

• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.133-152
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• 1998

The central composite design is widely used in the response surface analysis, because it can fit the second order model with small experimental points. In practice, the experimental data are not always obtained on all the points. When there are missing observations, many problems due to the missing cells can occur. In this paper, the influence of a missing cell on the central composite design is discussed. First, the influences of a missing cell on the variances of estimated regression coefficents are compared as $\alpha$ varies. Second, how the average predition variance is affected by a missing sell is discussed. And the influence on rotatability is investigated. Third, the influence of a missing cell on optimality, especially on D-optimality and A-optimality, is examined.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.267-280
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• 2007

Various single-valued design optimality criteria such as D-, G-, and V-optimality are used often in constructing optimal experimental designs for mixture experiments in a constrained region R where lower and upper bound constraints are imposed on the ingredients proportions. Even though they are optimal in the strict sense of particular optimality criterion used, it is known that their performance is unsatisfactory with respect to the prediction capability over a constrained region. (Vining et at., 1993; Khuri et at., 1999) We assume the quadratic polynomial model as the mixture response surface model and are interested in finding efficient designs in the constrained design space for a mixture. In this paper, we make an expanded list of candidate design points by adding interior points to the extreme vertices, edge midpoints, constrained face centroids and the overall centroid. Then, we want to propose a robust design with respect to D-optimality, G-optimality, V-optimality and distance-based U-optimality. Comparing scaled prediction variance quantile plots (SPVQP) of robust designs with that of recommended designs in Khuri et al. (1999) and Vining et al. (1993) in the well-known examples of a four-component fertilizer experiment as well as McLean and Anderson's Railroad Flare Experiment, robust designs turned out to be superior to those recommended designs.

• Journal of Applied Reliability
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• v.17 no.2
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• pp.129-135
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• 2017

Purpose: This article provides step-stress accelerated degradation test (ADT) plans based on the Wiener process. Method: Step-stress levels and the stress change times are determined based on the D-optimality criteria to develop test plans. Further, a simple grid search method is provided for obtaining the optimal test plan. Results: Based on the solution procedure, ADT plans which include the stress levels and change times are developed for conducting the reliability test. Conclusion: Optimal step-stress ADT plans are provided for the case where the number of measurements is small.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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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.