• 경영과학
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• 제10권1호
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• pp.193-205
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• 1993

This paper presents a mathematical model for a class of vertical integration decisions. The problem structure of interest consists of raw material vendors, components suppliers, components processing plants, final product (assembly) plants and external components buyers. Economic feasibility of operating components plants instead of keeping outside suppliers is our major concern. The model also determines assignment of product lines and production volumes to each open plant considering the cost impacts of economies of scale and plant complexity. The problem formulation leads to a concave, mixed integer mathematical program. Given the state of the art of nonlinear programming techniques, it is often not possible to find global optima for reasonably sized such problems. We developed an optimization solution algorithm within the framework of Benders decomposition for the case of a piecewise linear concave cost function. It is shown that our algorithm generates optimal solutions efficiently.

• 한국경영과학회지
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• 제32권3호
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• pp.47-61
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• 2007

This paper presents two elimination methods of subtours, which is obtained by applying the Out-of-Kilter algorithm to the sequential ordering problem (SOP) to produce a feasible solution for the SOP. Since the SOP is a kind of asymmetric traveling salesman problem (ATSP) with precedence constraints, we can apply the Out-of-Kilter algorithm to the SOP by relaxing the precedence constraints. Instead of patching subtours, both of two elimination methods construct a feasible solution of the SOP by using arcs constructing the subtours, and they improve solution by running 3-opt and 4-opt at each iteration. We also use a perturbation method. cost relaxation to explore a global solution. Six cases from two elimination methods are presented and their experimental results are compared to each other. The proposed algorithm found 32 best known solutions out of the 34 instances from the TSPLIB in a reasonable time.

• 한국항해항만학회지
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• 제33권2호
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• pp.143-151
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• 2009

The field of vehicle routing is currently growing rapidly because of many actual applications in truckload and less than truckload trucking, courier services, door to door services, and many other problems that generally hinder the optimization of transportation costs in a logistics network. The rapidly increasing number of customers in such a network has caused problems such as difficulty in cost optimization in terms of getting a global optimum solution in an acceptable time. Fast algorithms are needed to find sufficient solutions in a limited time that can be used for real time scheduling. In this paper, the nearest L-method (NLNM) is proposed to obtain a vehicle routing solution. String neighbors of different lengths were chosen, tested and compared. The applied de crossing procedure is meant to solve the routes by NLNM by giving a better solution and shorter computation time than that of NLNM with long string neighbors.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 C
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• pp.844-846
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• 1998

In this study, an adaptive evolutionary computation(AEC), which uses adaptively a genetic algorithm having global searching capability and an evolution strategy having local searching capability with different methodologies, is suggested. This paper develops AEC for solving ELD problem with piecewise quadratic cost function. Numerical results show that the proposed AEC can provide accurate dispatch solutions within reasonable time for the ELD problem with piecewise quadratic cost function.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1996년도 봄 학술발표회 논문집
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• pp.47-53
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• 1996

An enhanced solution recovery method for recovering accurate derivatives such as moments, or shears, from finite element solutions for $C^{0}$ beam and plate is presented. In the enhanced method, the square of the residuals in the equilibrium equations is included. Results are compared with those of standard Zienkiewicz-Zhu methods. Numerical examples show that in the global projection, the enhanced technique improves the accuracy of projected solution significantly. In the local projection, the enhanced method circumvents the numerical ill-conditioning which occurs in some meshes, and usually recovers derivatives with better accuracy.y.

• 전산구조공학
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• 제2권2호
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• pp.73-83
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• 1989

2차원적인 유한요소들을 각 절점에서 6개의 자요도를 갖는 3차원인 입체로 결합함으로써, 횡하중을 받고 있는 합성 쉘 구조를 해석할 수 있는 프로그램 [MSSLL]을 개발하였다. 전체 구조물이 여러개의 반복되는 Substructure들로 이루어졌을 때에는, 인력의 소모를 극소화하고 계산시간을 절약할 수 있도록 해석과정에 Substructuring 기법을 본 프로그램에 도입하였다. 프로그램의 신뢰도를 확인하기 위하여 본 프로그램에 의한 해석결과와 다른 방법에 의한 결과를 비교분석 하였으며, 지진력을 받고 있는 8개의 개별 원추들로 구성된 쉘 구조의 거동에 대한 높이-경간비의 영향을 규명하기 위하여 변수연구를 수행하였다.

• Smart Structures and Systems
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• 제15권3호
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.141-146
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• 1999

A new method, so called MMA(Method of Moving Asymptotes) was applied to the optimization problems of non-linear functions and non-linear structures. In each step of the iterative process, tile MMA generates a strictly convex approximation subproblems and solves them by using the dual problems. The generation of these subproblems is controlled by so called 'moving asymptotes', which may both make no oscillation and speed up tile convergence rate of optimization process. By contrast in generalized dual function, the generated function by MMA is always explicit type. Both the objective and behaviour constraints which were approximated are optimized by dual function. As the results of some examples, it was found that this method is very effective to obtain the global solution for problems with many local solutions. Also it was found that MMA is a very effective approximate method using the original function and its 1st derivatives.

• International Journal of Aerospace System Engineering
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• 제2권2호
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• pp.10-14
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• 2015

To design airfoils for novel airplanes, new knowledge of aerodynamics is required. In this study, modified Parametric SECtion (PARSEC) which is a airfoil representation is applied to airfoil design using a multi-objective genetic algorithm to obtain an optimal airfoil for consideration in the development of a Martian airplane. In this study, an airfoil that can obtain a sufficient lift and glide ratio under lower thrust is considered. The objective functions are to maximize maximum lift-to-drag ratio and to maximize the trailing edge thickness. In this way, information on the low Reynolds number airfoil could be extracted efficiently. The optimization results suggest that the airfoil with a sharper thickness at the leading edge and higher camber at the trailing edge is more suitable for a Martian airplane. In addition, several solutions which has thicker trailing edge thickness were found.

• 전자공학회논문지B
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• 제28B권10호
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• pp.761-770
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• 1991

This paper suggests a measure constraint locus for characterization of the performance of a subtask for a redundant robot. The measure constraint locus are the loci of points satisfying the necessary constraint for optimality of measure in the joint configuration space. To uniquely obtain an inverse kinematic solution, one must consider both measure constraint locus and self-motion manifolds which are set of homogeneous solutions. Using measure constraint locus for maniqulability measure, the invertible workspace without singularities and the topological property of the configuration space for linding equilibrium configurations are analyzed. We discuss some limitations based on the topological arguments of measure constraint locus, of the inverse kinematic algorithm for a cyclic task. And the inverse kinematic algorithm using global maxima on self-motion manifolds is proposed and its property is studied.