• Journal of the Korean Mathematical Society
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• v.35 no.2
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• pp.259-268
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• 1998

In this paper the stochastic multiple objective programming problems where the right-hand-side of the constraints is stochastic are considered. We define the equivalent scalar-valued problem and study the stability of the equivalent scalar-valued problem with respect to the weight parameters and probability mesures under reasonable assumptions.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.95.1-95
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• 2001

This paper is concerned with a novel S-stability (stochastic-stability) concept in linear time-invariant stochastic systems, where a stochastic mode in dynamics depends on both the external disturbance and the inner-parameter variations. This leads to an EAG (eigenstructure assignment gaussian) problem; that is, the problem of associating S-eigenvalues (stochastic-eigenvalues), S-eigenvectors (stochastic-eigenvectors), and their PDFs (probability density functions) with the stochastic information of the systems with the required stochastic specifications. These results explicitly characterize how S-eigenvalues, S-eigenvectors and their PDFs in the complex plane may impose S-stability on stochastic systems.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.162-172
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• 2021

This paper proposes stochastic methods to find an approximate solution for the L²-Wasserstein least squares problem of Gaussian measures. The variable for the problem is in a set of positive definite matrices. The first proposed stochastic method is a type of classical stochastic gradient methods combined with projection and the second one is a type of variance reduced methods with projection. Their global convergence are analyzed by using the framework of proximal stochastic gradient methods. The convergence of the classical stochastic gradient method combined with projection is established by using diminishing learning rate rule in which the learning rate decreases as the epoch increases but that of the variance reduced method with projection can be established by using constant learning rate. The numerical results show that the present algorithms with a proper learning rate outperforms a gradient projection method.

• Structural Engineering and Mechanics
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• v.39 no.4
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• pp.541-558
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• 2011

This paper presents an analysis of stochastic eigenvalue problem of plane bar structures. Particular attention is paid to the effect of spatial variations of the flexural properties of the structure on the first four eigenvalues. The problem of spatial variations of the structure properties and their effect on the first four eigenvalues is analyzed in detail. The stochastic eigenvalue problem was solved independently by stochastic finite element method (stochastic FEM) and Monte Carlo techniques. It was revealed that the spatial variations of the structural parameters along the structure may substantially affect the eigenvalues with quite wide gap between the two extreme cases of zero- and full-correlation. This is particularly evident for the multi-segment structures for which technology may dictate natural bounds of zero- and full-correlation cases.

• Korean Management Science Review
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• v.17 no.2
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• pp.175-187
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• 2000

The stochastic vehicle routing problem (VRP) is a problem of growing importance since it includes a reality that the deterministic VRP does not have. The stochastic VRP arises whenever some elements of the problem are random. Common examples are stochastic service quantities and stochastic travel times. The solution methodologies for the stochastic VRP are very intricate and regarded as computationally intractable. Even heuristics are hard to develope and implement. On possible way of solving it is to apply a solution for the deterministic VRP. This paper presents a performance evaluation of four simple heuristic for the deterministic VRP is a stochastic environment. The heuristics are modified to consider the time window constraints. The computational results show that some of them perform very well in different cases of the stochastic VRP.

• Coupled systems mechanics
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• v.11 no.2
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• pp.167-198
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• 2022

In this paper we deal with classical instability problems of heterogeneous Euler beam under conservative loading. It is chosen as the model problem to systematically present several possible solution methods from simplest deterministic to more complex stochastic approach, both of which that can handle more complex engineering problems. We first present classical analytic solution along with rigorous definition of the classical Euler buckling problem starting from homogeneous beam with either simplified linearized theory or the most general geometrically exact beam theory. We then present the numerical solution to this problem by using reduced model constructed by discrete approximation based upon the weak form of the instability problem featuring von Karman (virtual) strain combined with the finite element method. We explain how such numerical approach can easily be adapted to solving instability problems much more complex than classical Euler's beam and in particular for heterogeneous beam, where analytic solution is not readily available. We finally present the stochastic approach making use of the Duffing oscillator, as the corresponding reduced model for heterogeneous Euler's beam within the dynamics framework. We show that such an approach allows computing probability density function quantifying all possible solutions to this instability problem. We conclude that increased computational cost of the stochastic framework is more than compensated by its ability to take into account beam material heterogeneities described in terms of fast oscillating stochastic process, which is typical of time evolution of internal variables describing plasticity and damage.

• Korean Management Science Review
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• v.15 no.1
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• pp.33-47
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• 1998

The facility location problem considered here is to determine facility location sites under future's uncertain demand. The objective of this paper is to propose a solution method and algorithm for a two-stage stochastic facility location problem. utilizing the Benders decomposition method. As a two-stage stochastic facility location problem is a large-scale and complex to solve, it is usually attempted to use a mean value problem rather than using a stochastic problem. Thus, the other objective is to study the relative error of objective function values between a stochastic problem and a mean value problem. The simulation result shows that the relative error of objective function values between two problems is relatively small, when a feasibility constraint is added to a facility location model.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.23-36
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• 2016

We consider a model that minimizes the total cost incurred by assigning available weapons to existing targets in order to reduce enemy threats, which is called the weapon target assignment problem (WTAP). This study addresses the stochastic versions of WTAP, in which data, such as the probability of destroying a target, are given randomly (i.e., data are identified with certain probability distributions). For each type of random data or parameter, we provide a stochastic optimization model on the basis of the expected value or scenario enumeration. In particular, when the probabilities of destroying targets depending on weapons are stochastic, we present a stochastic programming formulation with a simple recourse. We show that the stochastic model can be transformed into a deterministic equivalent mixed integer programming model under a certain discrete probability distribution of randomness. We solve the stochastic model to obtain an optimal solution via the mixed integer programming model and compare this solution with that of the deterministic model.

• Journal of the military operations research society of Korea
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• v.31 no.2
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• pp.28-44
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• 2005

The previous studies approach the field artillery fire scheduling problem as deterministic and do not explicitly include information on the potential scenario changes. Unfortunately, the effort used to optimize fire sequences and reduce the total time of engagement is often inefficient as the collected military intelligence changes. Instead of modeling the fire sequencing problem as deterministic model, we consider a stochastic artillery fire scheduling model and devise a solution methodology to integrate possible enemy attack scenarios in the evaluation of artillery fire sequences. The goal is to use that information to find robust solutions that withstand disruptions in a better way, Such an approach is important because we can proactively consider the effects of certain unique scheduling decisions. By identifying more robust schedules, cascading delay effects will be minimized. In this paper we describe our stochastic model for the field artillery fire sequencing problem and offer revised robust stochastic model which considers worst scenario first. The robust stochastic model makes the solution more stable than the general two-stage stochastic model and also reduces the computational cost dramatically. We present computational results demonstrating the effectiveness of our proposed method by EVPI, VSS, and Variances.

• Structural Engineering and Mechanics
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• v.28 no.3
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• pp.281-294
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• 2008

In this paper, linear elastic isotropic structures under the effects of both stochastic operators and stochastic excitations are studied. The analysis utilizes the spectral stochastic finite elements (SSFEM) with its two main expansions namely; Neumann and Homogeneous Chaos expansions. The random excitation and the random operator fields are assumed to be second order stochastic processes. The formulations are obtained for the system solution of the two dimensional problems of plane strain and plate bending structures under stochastic loading and relevant rigidity using the previously mentioned expansions. Two finite element programs were developed to incorporate such formulations. Two illustrative examples are introduced: the first is a reinforced concrete culvert with stochastic rigidity subjected to a stochastic load where the culvert is modeled as plane strain problem. The second example is a simply supported square reinforced concrete slab subjected to out of plane loading in which the slab flexural rigidity and the applied load are considered stochastic. In each of the two examples, the first two statistical moments of displacement are evaluated using both expansions. The probability density function of the structure response of each problem is obtained using Homogeneous Chaos expansion.