• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.196-202
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• 2000

In the precision point synthesis of mechanisms, it is usually required to solve a system of polynomial equations. With the aid of efficient algorithms such as elimination, it is possible to obtain all the solutions of the equations in the complex domain. But among these solutions only real values can be used fur real mechanisms, while imaginary ones are liable to be discarded. In this article, a method is presented, which leads the imaginary solutions to real domain permitting slight alteration of prescribed positions and eventually increases the number of feasible mechanisms satisfying the desired motion approximately. Two synthesis problems of planar 4-bar path generation and spatial 7-bar motion generation are given to verify the proposed method.

• ETRI Journal
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• v.24 no.2
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• pp.131-141
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• 2002

This paper considers a routing and wavelength assignment problem (RWAP) for the implementation of efficient Wavelength Division Multiplexing all-optical mesh networks without wavelength conversion. For a given physical network and required connections, the solution to the RWAP consists in how to select a suitable path and wavelength among the many possible choices for each connection so that no two paths using the same wavelength pass through the same link, while minimizing the number of required wavelengths. We introduce an integer programming formulation of the RWAP, which has an exponential number of variables, and propose an algorithm to solve it based on the column generation technique. The proposed algorithm can yield high quality solutions and tight lower bounds at the same time. Though the proposed algorithm cannot guarantee optimal solutions, computational results show that the algorithm yields provably good solutions within a reasonable time.

• Industrial Engineering and Management Systems
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• v.8 no.1
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• pp.29-36
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• 2009

We present two local-search based metaheuristics for the multi-source capacitated facility location problem. In such a problem, each customer's demand can be supplied by one or more facilities. The problem is NP-hard and the number of locations in the optimal solution is unknown. To keep the search process effective, the proposed methods adopt the following features: (1) a multi-exchange neighborhood structure, (2) a tabu list that keeps track of recently visited solutions, and (3) a multi-start to enhance the diversified search paths. The transportation simplex method is applied in an efficient manner to obtain the optimal solutions to neighbors of the current solution under the algorithm framework. Two in-and-out selection rules are also proposed in the algorithms with the purpose of finding promising solutions in a short computational time. Our computational results for some of the benchmark instances, as well as some instances generated using a method in the literature, have demonstrated the effectiveness of this approach.

• IE interfaces
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• v.20 no.4
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• pp.504-514
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• 2007

The multicast routing problem lies in the composition of a multicast routing tree including a source node and multiple destinations. There is a trade-off relationship between cost and delay, and the multicast routing problem of optimizing these two conditions at the same time is a difficult problem to solve and it belongs to a multi-objective optimization problem (MOOP). A multi-objective genetic algorithm (MOGA) is efficient to solve MOOP. A micro-genetic algorithm(${\mu}GA$) is a genetic algorithm with a very small population and a reinitialization process, and it is faster than a simple genetic algorithm (SGA). We propose a multi-objective micro-genetic algorithm (MO${\mu}GA$) that combines a MOGA and a ${\mu}GA$ to find optimal solutions (Pareto optimal solutions) of multicast routing problems. Computational results of a MO${\mu}GA$ show fast convergence and give better solutions for the same amount of computation than a MOGA.

• Structural Engineering and Mechanics
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• v.38 no.5
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• pp.549-571
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• 2011

This paper presents analytical solutions for skewed thick plates under transverse loading that have previously been unreported in the literature. The thick plate solution is obtained in a framework of an oblique coordinate system. The governing equation is first derived in the oblique coordinate system, and the solution is obtained using deflection and rotation as partial derivatives of a potential function developed in this research. The solution technique is applied to three illustrative application examples, and the results are compared with numerical solutions in the literature and those derived from the commercial finite element analysis package ANSYS 11. These results are in excellent agreement. The present solution may also be used to model skewed structures such as skewed bridges, to facilitate efficient routine design or evaluation analyses, and to form special elements for finite element analysis. At the same time, the analytical solution developed in this research could be used to develop methods to address post-buckling and dynamic problems.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2773-2781
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• 1993

Laplace's equation is, perhaps, the most important equation, which governs various kinds of physical phenomena. Due to its importance, there have been several numerical techniques such as the finite element method, the finite difference method, and the boundary element method. However, these techniques do not appear very effective as they require a substantial amount of numerical calculation. In this paper, we develop a new most efficient technique based on analytic solutions for Laplace's equation in some convex polygons. Although a similar approach was used for the same problem, the present technique is unique as it solves directly Laplace's equation with the utilization of analytical solutions.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.533-549
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• 1996

This paper is concerned with a sequencing problem in mixed model assembly lines, which is important to efficient utilization of the lines. In the problem, we deal with the two objectives of minimizing the risk of stoppage and leveling part usage, and consider sequence-dependent setup time. In this paper, we present a genetic algorithm(GA) suitable for the multi-objective optimization problem. The aim of multi-objective optimization problems is to find all possible non-dominated solutions. The proposed algorithm is compared with existing multi-objective GAs such as vector evaluated GA, Pareto GA, and niched Pareto GA. The results show that our algorithm outperforms the compared algorithms in finding good solutions and diverse non-dominated solutions.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.523-542
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• 2014

One-dimensional arrays with subscripts formed by induction variables in real programs appear quite frequently. For most famous data dependence testing methods, checking if integer-valued solutions exist for one-dimensional arrays with references created by induction variable is very difficult. The I test, which is a refined combination of the GCD and Banerjee tests, is an efficient and precise data dependence testing technique to compute if integer-valued solutions exist for one-dimensional arrays with constant bounds and single increments. In this paper, the non-continuous I test, which is an extension of the I test, is proposed to figure out whether there are integer-valued solutions for one-dimensional arrays with constant bounds and non-sing ularincrements or not. Experiments with the benchmarks that have been cited from Livermore and Vector Loop, reveal that there are definitive results for 67 pairs of one-dimensional arrays that were tested.

• Coupled systems mechanics
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• v.10 no.1
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• pp.79-102
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• 2021

In this paper we deal with instability problems of structures under nonconservative loading. It is shown that such class of problems should be analyzed in dynamics framework. Next to analytic solutions, provided for several simple problems, we show how to obtain the numerical solutions to more complex problems in efficient manner by using the finite element method. In particular, the numerical solution is obtained by using a modified Euler-Bernoulli beam finite element that includes the von Karman (virtual) strain in order to capture linearized instabilities (or Euler buckling). We next generalize the numerical solution to instability problems that include shear deformation by using the Timoshenko beam finite element. The proposed numerical beam models are validated against the corresponding analytic solutions.

• The Journal of Information Technology
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• v.3 no.2
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• pp.73-85
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• 2000

The efficient algorithms are suggested in this study for solving the multicommodity network flow problems applied to Communications Systems. These problems are typical NP-complete optimization problems that require integer solution and in which the computational complexity increases numerically in appropriate with the problem size. Although the suggested algorithms are not absolutely optimal, they are developed for computationally efficient and produce near-optimal and primal integral solutions. We supplement the traditional Lagrangian method with a price-directive decomposition. It proceeded as follows. First, A primal heuristic from which good initial feasible solutions can be obtained is developed. Second, the dual is initialized using marginal values from the primal heuristic. Generally, the Lagrangian optimization is conducted from a naive dual solution which is set as ${\lambda}=0$. The dual optimization converged very slowly because these values have sort of gaps from the optimum. Better dual solutions improve the primal solution, and better primal bounds improve the step size used by the dual optimization. Third, a limitation that the Lagrangian decomposition approach has Is dealt with. Because this method is dual based, the solution need not converge to the optimal solution in the multicommodity network problem. So as to adjust relaxed solution to a feasible one, we made efficient re-allocation heuristic. In addition, the computational performances of various versions of the developed algorithms are compared and evaluated. First, commercial LP software, LINGO 4.0 extended version for LINDO system is utilized for the purpose of implementation that is robust and efficient. Tested problem sets are generated randomly Numerical results on randomly generated examples demonstrate that our algorithm is near-optimal (< 2% from the optimum) and has a quite computational efficiency.