• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.59-64
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• 2011

In 2001, the notion of a fuzzy poset defined on a set X via a triplet (L, G, I) of functions with domain X ${\times}$ X and range [0, 1] satisfying a special condition L+G+I = 1 is introduced by J. Negger and Hee Sik Kim, where L is the 'less than' function, G is the 'greater than' function, and I is the 'incomparable to' function. Using this approach, we are able to define a special class of fuzzy posets, and define the 'skeleton' of a fuzzy poset in view of major relation. In this sense, we define the linear discrepancy of a fuzzy poset of size n as the minimum value of all maximum of I(x, y)${\mid}$f(x)-f(y)${\mid}$ for f ${\in}$ F and x, y ${\in}$ X with I(x, y) > $\frac{1}{2}$, where F is the set of all injective order-preserving maps from the fuzzy poset to the set of positive integers. We first show that the definition is well-defined. Then, it is shown that the optimality appears at the same injective order-preserving maps in both cases of a fuzzy poset and its skeleton if the linear discrepancy of a skeleton of a fuzzy poset is 1.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.220-227
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• 2018

The cooperative game theory consists of a set of players and utility function that has positive values for a subset of players, called coalition, in the game. The purpose of cost allocation method is to allocate the relevant cost among game players in a fair and rational way. Therefore, cost allocation method based on cooperative game theory has been applied in many areas for fair and reasonable cost allocation. On the other hand, the desirable characteristics of the cost allocation method are Pareto optimality, rationality, and marginality. Pareto optimality means that costs are entirely paid by participating players. Rationality means that by joining the grand coalition, players do not pay more than they would if they chose to be part of any smaller coalition of players. Marginality means that players are charged at least enough to cover their marginal costs. If these characteristics are all met, the solution of cost allocation method exists in the core. In this study, proportional method is applied to EOQ inventory game and EPQ inventory game with shortage. Proportional method is a method that allocates costs proportionally to a certain allocator. This method has been applied to a variety of problems because of its convenience and simple calculations. However, depending on what the allocator is used for, the proportional method has a weakness that its solution may not exist in the core. Three allocators such as demand, marginal cost, and cost are considered. We prove that the solution of the proportional method to demand and the proportional method to marginal cost for EOQ game and EPQ game with shortage is in the core. The counterexample also shows that the solution of the proportional method to cost does not exist in the core.

• Journal of Korean Society for Quality Management
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• v.23 no.1
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• pp.15-28
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• 1995

We consider a step-stress life testing which is devised for a two-component parallel system with considerably long life time. To describe such a system, we use an exponential distribution as the survival function. The lift distribution is assumed between the log mean life time and the stress with the cumulative exposure model. The criterion for optimality is to minimize the sum of the variances of the maximum likelihood estimators of the mean life times of each part under the normal stress.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.527-538
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• 2019

This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.201-210
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• 2009

A loss minimizing controller is developed for a fuel cell electric vehicle (FCEV) permanent magnet synchronous motor (PMSM). The PMSM losses are modeled by some experimental equations. Applying Lagrangian to the loss function, a necessary condition for the optimality appears to be a fourth order polynomial, and the loss minimizing solutions are obtained by a simple numerical approach. On the other hand, the loss minimizing solutions are found by scanning the motor loss in the entire operating region. The two results agree well. The loss minimizing current sets for given torque and speed are made into a table, which is utilized as a look-up in the current control loop.

• 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.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.54-60
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• 2018

This paper contains the multi-mission scheduling optimization of UAV within a given operating time. Mission scheduling optimization problem is one of combinatorial optimization, and it has been shown to be NP-hard(non-deterministic polynomial-time hardness). In this problem, as the size of the problem increases, the computation time increases dramatically. So, we applied the genetic algorithm to this problem. For the application, we set the mission scenario, objective function, and constraints, and then, performed simulation with MATLAB. After 1000 case simulation, we evaluate the optimality and computing time in comparison with global optimum from MILP(Mixed Integer Linear Programming).

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.124-126
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• 2002

The general capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. In this paper, the method employing the chaos search algorithm is proposed to solve optimal capacitor placement problem with reducing computational effort and enhancing optimality of the solution. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 9 buses and 69 buses system to illustrate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.149-154
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• 1990

In this paper, simulation results of a robust digital tracking controller on a robotic manipulator are presented. The objective is to follow a ramp reference input with zero steady state error in the presence of a disturbance and system parameter variations. Some of the difficulties are caused by the Coulomb frictions, the disturbance due to the gravitational pull, the spring effect of a link between the drive motor and the manipulator arm. Another difficulty is that, because of the non-differentiable Coulomb friction, the digital control system cannot be represented as a discrete system. It is thus necessary to design the controller based on a discrete-continuous hybrid model. The controller is based on feeding back the state variables and augmenting the system by addition discrete integrators. The feedback gain parameters are obtained by applying the quadratic optimal control theory and then choosing the new weighting matrices to eliminate the limit cycle by using the describing function method for hybrid system.