• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.13-19
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• 1992

MODM(multiobjective decision-making)problem is very complex system for the analysist and decision maker. Therefore, it requires suitable MODM method to solve multiobjective decision-making problem. This paper presents an interactive fuzzy decision making method for solving multiobjective nonlinear programming problems with fuzzy goals and $\alpha$-cut set of fuzzy numbers. In our interactive method, if the decision maker specifies the degree $\alpha$of the objective value and the imprecise goals, λ-mux problem is solved. To examplify the proposed method, an interactive computer programming written in FORTRAN and an illustrate numerical example along with computer outputs are presented.

• Journal of the Korean Institute of Navigation
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• v.22 no.4
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• pp.15-19
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• 1998

This paper concerns a bulk or semibulk cargo ship scheduling problem with a single loading port. This type of ship scheduling problem is frequently needed in real world for carrying minerals or agricultural produce from a major single production zone to many destinations scattered over a large area of the world. The first optimization model for this problem was introduced by Ronen (1986) as a nonlinear mixed integer program. The model developed in this paper is an improvement of his model in the sense that nonlinearities and numerous unnecessary integer variables have been eliminated. By this improvement we could expect real world instances of moderate sizes to be solved optimal solutions by commercial integer programming software. Similarity between the ship scheduling model and the capacitated facility location model is also discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.107-112
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• 2015

This paper introduces an evolutionary nonlinear regression based compensation technique for the short-range prediction of wind speed using AWS(Automatic Weather Station) data. Development of an efficient MOS(Model Output Statistics) is necessary to correct systematic errors of the model, but a linear regression based MOS is hard to manage an irregular nature of weather prediction. In order to solve the problem, a nonlinear and symbolic regression method using GP(Genetic Programming) is suggested for a development of MOS wind forecast guidance. Also FCM(Fuzzy C-Means) clustering is adopted to mitigate bias of wind speed data. The purpose of this study is to evaluate the accuracy of the estimation by a GP based nonlinear MOS for 3 days prediction of wind speed in South Korean regions. This method is then compared to the UM model and has shown superior results. Data for 2007-2009, 2011 is used for training, and 2012 is used for testing.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.1
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• pp.301-309
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• 1995

Shape optimal design of an excavator boom to minimize weight can be formulated as a nonlinear programming problem with an automesh refinement carried out by using the finite element method. The design variables are the radii and the coordinates of the circle to describe the excavator boundary shape. In addition to the displacement and stress constraints, geometric constraints are imposed such that the nodes cannot cross the certain range. The optimum design is obtained by using the PLBA nonlinear programming code. The sensitivity derivatives are calculated using the semi-analytical scheme. Numerical results of an excavator boom show potential for weight reduction of 4.4%(65.6 kgf) when considering the displacement, stress and geometric constraints.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.406-412
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• 1996

Optimal trajectory for a robot manipulator minimizing actuator torques or energy consumption in a fixed traveling time is obtained in the presence of obstacles. All joint displacements are represented in finite terms of Fourier cosine series and the coefficients of the series are obtained optimally by nonlinear programming. Thus, the geometric path need not be prespecified and the full dynamic model is employed. To avoid the obstacles, the concept of penalty area is newly introduced and this penalty area is included in the performance index with an appropriate weighting coefficient. This optimal trajectory will be useful as a geometric path in the minimum-time trajectory planning problem.

• Journal of the military operations research society of Korea
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• v.28 no.1
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• pp.47-66
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• 2002

Instead of using signal-to-noise ratio, we attempt to optimize both the mean and variance responses using dual response optimization technique. The alternative experimental strategy analyzes a robust parameter design problem to obtain the best settings that give a target condition on the mean while minimizing its variance. The mean and variance are treated as the two responses of interest to be optimized. Unlike to the crossed array and combined array approaches, our experimental setup requires replicated runs for each control factor's treatment under noise sampling. When the postulated response models are true, they enable the coefficients to be estimated and the desired performance measure to be analyzed more efficiently. The procedure and illustrative example are given for the dual response optimization techniques of nonlinear goal programming.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.65-75
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• 2000

Cellular manufacturing(CM) is a philosophy and innovation to improve manufacturing productivity and flexibility. Cell formation(CF), the first and key problem faced in designing an effective CM system, is a process whereby parts with similar design features or Processing requirements are grouped into part families, and the corresponding machines into machine cells. Cell formation solutions often contain exceptional elements(EEs). EE create interactions between two manufacturing cells. A policy dealing with EEs considers minimizing the total costs of three important costs; (1)intercellular transfer (2)machine duplication and (3)subcontracting. This paper presents an effective cell formation method with fuzzy nonlinear mixed-integer programming simultaneously to form manufacturing cells and to minimize the total costs of eliminating exceptional elements.

• Journal of applied mathematics & informatics
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• v.32 no.3_4
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• pp.359-375
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• 2014

In this paper, a multiobjective nondifferentiable fractional programming problem (MFP) is considered where the objective function contains a term involving the support function of a compact convex set. A vector valued (generalized) ${\alpha}$-univex function is defined to extend the concept of a real valued (generalized) ${\alpha}$-univex function. Using these functions, sufficient optimality criteria are obtained for a feasible solution of (MFP) to be an efficient or weakly efficient solution of (MFP). Duality results are obtained for a Mond-Weir type dual under (generalized) ${\alpha}$-univexity assumptions.

• 전기의세계
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• v.30 no.6
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• pp.375-385
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• 1981

New algorithms are derived for nonlinear programming problems which are characterized by their large variables and equality and inequality constraints. The algorithms are based upon the introduction of the Dependent-Variable-Elimination method, Independent-Variable-Reduction method, Optimally-Ordered-Triangular-Factorization method, Equality-Inequality-Sequential-Satisfaction method, etc. For a case study problem relating to the optimal determination of load flow in a 10-bus, 13-line sample power system, several approaches are undertaken, such as SUMT, Lagrange's Multiplier method, sequential applications of linear and quadratic programming method. For applying the linear programming method, the conventional simplex algorithm is modified to the large-system-oriented one by the introduction of the Two-Phase method and Variable-Upper-Bounding method, thus resulting in remarkable savings in memory requirements and computing time. The case study shows the validity and effectivity of the algorithms presented herein.

• Computational Structural Engineering
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• v.10 no.2
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• pp.255-263
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• 1997

The optimum design of most structural systems used in practice requires considering design variables as discrete quantities. The present paper shows that the linear approximation method is very effective as a tool for the discrete optimum designs of unsymmetric composite laminates. The formulated design problem is subjected to a multiple in-plane loading condition due to shear and axial forces, bending and twisting moments, which is controlled by maximum strain criterion for each of the plys of a composite laminate. As an initial approach, the process of continuous variable optimization by FDM is required only once in operating discrete optimization. The nonlinear discrete optimization problem that has the discrete and continuous variables is transformed into the mixed integer programming problem by SLDP. In numerical examples, the discrete optimum solutions for the unsymmetric composite laminates consisted of six plys according to rotated stacking sequence were found, and then compared the results with the nonlinear branch and bound method to verify the efficiency of present method.