• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.52-63
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• 2017

The inventory level of concurrent spare parts (CSP) has a significant impact on the availability of a weapon system. A failure rate function might be of particular importance in deciding the CSP inventory level. We developed a CSP optimization model which provides a compromise between purchase costs and shortage costs on the basis of the Weibull and the exponential failure rate functions, assuming that a failure occurs according to the (non-) homogeneous Poisson process. Computational experiments using the data obtained from the Korean Navy identified that, throughout the initial provisioning period, the optimization model using the exponential failure rate tended to overestimate the optimal CSP level, leading to higher purchase costs than the one using the Weibull failure rate. A Pareto optimality was conducted to find an optimal combination of these two failure rate functions as input parameters to the model, and this provides a practical solution for logistics managers.

• Structural Engineering and Mechanics
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• v.5 no.5
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• pp.565-576
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• 1997

The material-based homogenization design method generates arbitrary topologies of initial structural design as well as reinforcement structural design by controlling the amount of material available. However, if a small volume constraint is specified in the design of Lightweight structures, thin and slender structures are usually obtained. For these structures stability becomes one of the most important requirements. Thus, to prevent overall buckling (that is, to increase stability), the objective of the design is to maximize the buckling load of a structure. In this paper, the buckling analysis is restricted to the linear buckling behavior of a structure. The global stability requirement is defined as a stiffness constraint, and determined by solving the eigenvalue problem. The optimality conditions to update the design variables are derived based on the sequential convex approximation method and the dual method. Illustrated examples are presented to validate the feasibility of this method in the design of structures.

• Journal of Korean Society for Quality Management
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• v.39 no.4
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• pp.480-485
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• 2011

This paper presents a spare ordering policy for preventive replacement with minimal repair. To analyze the ordering policy, the failure process is modeled by a non-homogeneous Poisson process. Introducing the ordering, repair, downtime, replacement costs and salvage value, we derive the expected cost effectiveness as a criterion of optimality when the lifetime and lead times for the regular and expedited orders are generally distributed random variables. It is shown that, under certain conditions, there exists a finite and unique optimum ordering time which maximizes the expected cost effectiveness. A numerical example is also included to explain the proposed model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.40-43
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• 2005

This paper presents the minimization of the fuel cost by optimal allocation of P-Q generation in a three-bus sample system. Derivation of the system loss sensitivities by optimization technique is introduced. The loss sensitivities are substituted into the optimality conditions and the optimal P-Q allocation is computed to obtain the minimal fuel cost.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.981-1000
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• 2009

This paper considers asset liability management problems when their deterministic equivalent formulations are general nonlinear optimization problems. The presented approach uses a nonmonotone trust region strategy for solving a sequence of unconstrained subproblems parameterized by a scalar parameter. The objective function of each unconstrained subproblem is an augmented penalty-barrier function that involves both primal and dual variables. Each subproblem is solved approximately. The algorithm does not restrict a monotonic decrease of the objective function value at each iteration. If a trial step is not accepted, the algorithm performs a non monotone line search to find a new acceptable point instead of resolving the subproblem. We prove that the algorithm globally converges to a point satisfying the second-order necessary optimality conditions.

• 전기의세계
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• v.26 no.6
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• pp.48-54
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• 1977

The object of this work is to study the optimal control strategy of constant speed characteristics for a D.C control motor under influence of disturbance. In the course of the analysis, the linearization and time invariance schemes on motor dynamics are presumed throughout under certain prescribed conditions and the performance measure for optimality is assumed to be quadratic in state and the control effort, with the initial and final time specified. When the motor speed is deviated from a stationary operating point by any external disturbance, the optimal continuous feedback control law is investigated by the application of the calculus of variation and realizability of the required control meachanism is suggested. Finally, the comparative study of the speed reasponses of the motor, with and without the optimal control effort is also presented to confirm the obtained results.

• Korean Journal of Mathematics
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• v.23 no.2
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• pp.293-312
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• 2015

We deal with a boundary control problem for the vorticity minimization, in which the ow is governed by the time-dependent two dimensional incompressible Navier-Stokes equations. We derive a mathematical formulation and a process for an appropriate control along the portion of the boundary to minimize the vorticity motion due to the ow in the fluid domain. After showing the existence of an optimal solution, we derive the optimality system for which optimal solutions may be determined. The differentiability of the state solution in regard to the control parameter shall be conjunct with the necessary conditions for the optimal solutions.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.356-357
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• 2018

Fuel-cell powered Railway Vehicle Propulsion Systems (RVPSs) are highly desirable due to environment friendly characteristics, and high efficiency of fuel cell (FC). Among various types, the faster start-up and optimality to frequent starts and stops of Polymer electrolyte membrane fuel cell (PEMFC) makes it well suited for propulsion systems. A comprehensive model of PEMFC with reflection of multi-physics behavior required to identify and validate its performance in real RVPSs. Thus this paper will model and simulate the PEMFC unit cell model: a detailed reflection of governing laws and account of dynamic conditions.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.

• Speech Sciences
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• v.11 no.4
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• pp.43-52
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• 2004

Model parameters in HMM based speech recognition systems are normally estimated using Maximum Likelihood Estimation(MLE). The MLE method is based mainly on the principle of statistical data fitting in terms of increasing the HMM likelihood. The optimality of this training criterion is conditioned on the availability of infinite amount of training data and the correct choice of model. However, in practice, neither of these conditions is satisfied. In this paper, we propose a training algorithm, MCE(Minimum Classification Error), to improve the performance of a speech recognizer detecting mispronunciation of a foreign language. During the conventional MLE(Maximum Likelihood Estimation) training, the model parameters are adjusted to increase the likelihood of the word strings corresponding to the training utterances without taking account of the probability of other possible word strings. In contrast to MLE, the MCE training scheme takes account of possible competing word hypotheses and tries to reduce the probability of incorrect hypotheses. The discriminant training method using MCE shows better recognition results than the MLE method does.