• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.2
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• pp.95-108
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• 1978

This paper discusses an application of mathematical programming techniques in the paper industry in determining optimal parent roll widths. Parent rolls are made from the reels produced at wide paper machines by slitting them to more manageable widths. The problem is finding a set of the slitting patterns that will minimize the trim loss involved in the sheeting operation. Two programming models, one linear and one mixed integer linear, are presented in this paper. Also presented are the computational experience, the model sensitivity, and the comparison of the optimal solutions with the simulated operational data.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.101-113
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• 1995

The past three decades have witnessed a tremendous growth is the literature on location proble. A mathematical formulation of uncapacitated plant location problem and the k-median as an integer program has proven very fruitful in the derivation of solution methods. Most of the successful algorithms for the problem are based on so-called "strong" linear programming relaxation. This is due to the fact that the strong linear programming relaxation provides a tight lower bound. In this paper we investigate the phenomenon with a structural analysis of the problem.e problem.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.1
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• pp.3-10
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• 1984

A materials acquisition planning (MAP) problem that involves the determination of how much to order of a number of different items from a number of different suppliers is considered. This particular problem is modelled as a nonlinear mixed integer programming problem. A solution procedure based upon the partition of variables is developed to handle the MAP problem. This solution procedure utilizes a modified Hooke-Jeeves Pattern Search procedure along with a linear programming simplex algorithm. An example problem is presented and the results of applying the suggested solution procedure to this problem are reported.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.71-74
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• 2014

A new classification framework called 'support feature machine' was introduced in [2] for analyzing medical data. Contrary to authors' claim, however, the proposed method is not designed to guarantee minimizing the use of the spatial feature variables. This paper mathematically remedies this drawback and provides comments on models from [2].

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.139-151
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• 2004

Kim et al. (2002) developed public use SAS-based software for two-way stratification design, which is called SOCSLP We describe the details of a new approach implemented using SOCSLP and key differences between the approach and the sampling schemes of Sitter and Skinner (1994) and Winkler (2001). In addition, a numerical example is given to compare those methods with respect to the probabilities of selecting sample arrays.

• Journal of Korean Society of Transportation
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• v.8 no.1
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• pp.41-54
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• 1990

The rapid increase in the freight movement in Korea demands the improvement of the freight transportation system both in quantity and in quality. In recent studies integrated freight terminals have been suggested as the most relevant physical facility that solves this problem. This paper is aiming at the efficiency of the freight transportation system in Korea via integrated freight terminals. We develop a mixed integer programming model to determine simultaneously the most efficient freight flow patterns as well as the optimal locations and sizes of the integrated freight terminal facilities. The results of the model implication is also presented.

• The Pure and Applied Mathematics
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• v.3 no.1
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• pp.73-81
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• 1996

Multiple objective programming has been a popular research area since 1970. The pervasiveness of multiple objective in decision problems have led to explosive growth during the 1980's. Several approaches (interactive methods, feasible direction methods, criterion weight space methods, Lagrange multiplies methods, etc) have been developed for solving decision problems having multiple objectives. However there are still many mathematically challengings including multiple objective integer, nonlinear optimization problems which require further mathematically oriented research. (omitted)

• Journal of the Korean Society of Marine Environment & Safety
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• v.6 no.1
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• pp.23-33
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• 2000

This paper is concerned with finding the global optimal solutions for the redundancy optimization problems in series-parallel systems related with system safety. This study transforms the difficult problem, which is classified as a nonlinear integer problem, into a 0/1 IP(Integer Programming) by using binary integer variables. And the global optimal solution to this problem can be easily obtained by applying GAMS (General Algebraic Modeling System) to the transformed 0/1 IP. From computational results, we notice that GA(Genetic Algorithm) to this problem, which is, to our knowledge, known as a best algorithm, is poor in many cases.

• IE interfaces
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• v.24 no.2
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• pp.151-155
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• 2011

In this study, we propose a signomial classification method with ₀-regularization (₀-)which seeks a sparse signomial function by solving a mixed-integer program to minimize the weighted sum of the ₀-norm of the coefficient vector of the resulting function and the $L_1$-norm of loss caused by the function. $SC_0$ gives an explicit description of the resulting function with a small number of terms in the original input space, which can be used for prediction purposes as well as interpretation purposes. We present a practical implementation of $SC_0$ based on the mixed-integer programming and the column generation procedure previously proposed for the signomial classification method with $SL_1$-regularization. Computational study shows that $SC_0$ gives competitive performance compared to other widely used learning methods for classification.

• Korean Management Science Review
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• v.28 no.2
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• pp.17-29
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• 2011

The purpose of this paper is to schedule elective surgery patients using a stochastic programming approach and to illustrate how operating room utilization behaves when a decision-maker varies costs associated with utilization. Because of the uncertainty in surgery durations, the underage and overage costs that a decision-maker considers plays an important role in allocating surgery cases into available operating room capacity. We formulate the problem as a stochastic mixed integer programming and propose a sampling-based approximation method for a computational purpose. Newsvendor model is employed to explain the results from numerical experiments that are conducted with the actual data from a hospital. The results show that the operating room utilization is more sensitive when the unit overtime cost is relatively larger than the unit cost for underutilized time.