• Korean Management Science Review
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• v.16 no.1
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• pp.1-9
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• 1999

The purpose of this paper is to develope efficient techniques for implementing the dual simplex method. In this paper we proposed one artificial row technique to get an initial dual feasible basic solution, a dual steepest-edge method coupled with a dropping row selection rule, and an anti-degeneracy technique which resembles the EXPAND procedure for the primal simplex method. The efficiency of the above techniques is shown by experiments. Finally, the dual simplex method is shown to be superior to the primal simplex method when it is used in the integer programming.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.217-225
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• 1999

Preprocessing is the essential technique in the implementation of the simplex method for large scale linear programming problems. In this research, we explained the effect of preprocessing in the simplex method, classified the techniques into four categories, and compared our results with those of HOPDM, CPLEX and Soplex by computational experiments. We also noted some implementing issues of preprocessing for the simplex method and the recovery of the optimal basis of the original problem from that of the preprocessed problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.249-253
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• 2006

We propose a new beamforming algorithm, which is based on simplex downhill optimization method in the presence of pilot channels in cdma2000 reverse-link, for the rake structure antenna array in DS/CDMA communication system. Our approach uses the desired signal(pilot) covariance matrix and the interference covariance matrix. The beamforming weights are made according to maximum SINR criteria using simplex downhill optimization procedure. Our proposed scheme provides lower computational load, better convergence speed, better performance than existingadaptive beamforming algorithm. The simplex downhill method is well suited to finding the optimal or sub-optimal weight vector, since they require only the value of the deterministic function to be optimized. The rake beamformer performances are also evaluated under several set of practical parameter values with regard to spatial channel model. We also compare the performance between conventional rake receiver and the proposed one under same receiving power.

• Korean Management Science Review
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• v.11 no.3
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• pp.13-26
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• 1994

In this paper we studied an integration scheme of some simplex algorithms and some efficient techniques to get the stable solution in linear programming code. And we developed a linear programming package (LPAK) by introducing this scheme and techniques. In LPAK three different algorithms were integrated, which were two primal simplex algorithms using Two phase method and big-M method respectively, and the dual simplex algorithm. LPAK introduces several heuristic techniques in each step of simplex method in order to enhance the stability and efficiency. They were new heuristic methods in structuring initial basis, choosing entering variable, choosing dropping variable and performing reinversion. The experimental results on the NETLIB problems showed that LPAK provided the stable solutions.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.7
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• pp.1-13
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• 2002

Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.541-552
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• 2002

Two global optimization methods, the SCE-UA method and the Annealing-Simplex(A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. In synthetic data study, 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The Downhill Simplex method was converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed, which puts more weight on the low flows.

• Korean Management Science Review
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• v.13 no.3
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• pp.105-113
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• 1996

Constructing an initial basis is an important process in the simplex method. An initial basis greatly affects the number of iterations of iterations and the execution time in the simplex method. The purpose of this paper is to construct a good initial basis. First, to avoid linear dependency among the chosen columns, an enhanced Gaussian elimination method and a method using non-duplicated nonzero elements are developed. Second, for an order to choose variables, the sparsity of the column is used. Experimenal results show that the proposed method can reduce the number of iterations and the execution time compared with Bixby's method by 12%.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.496-506
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• 2006

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.1
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• pp.27-38
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• 1999

In this paper, Primal-Interior Dual-Simplex method(PIDS) and Dual-Interior Primal-Simplex method(DIPS) are developed for the general bounded linear programming. Two methods were implemented and compared with other pricing techniques for the Netlib. linear programming problems. For the PIDS, it shows superior performance to both most nagative rule and dual steepest-edge method since it practically reduces degenerate iterations and has property to reduce the problem. For the DIPS, pt requires less iterations and computational time than least reduced cost method. but it shows inferior performance to the dynamic primal steepest-edge method.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.27-34
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• 2000

The definition of flatness is given by ISO, ANSI, KS, etc. but those standards don't mention about the specific methods for the flatness. So various solution models that are based on the Minimum Zone Method have been proposed as an optimization problem for the minimax curve fitting. But it has been rare to compare some optimization algorithms to make a guideline for choosing better algorithms in this field. Hence this paper examined and compared Genetic Algorithm and Simplex Method to the evaluation of flatness. As a result, Genetic Algorithm gave the better or equal flatness than Simplex Method but it has the inefficiency caused from the large number of iteration. Therefore, in the future, another researches about alternative algorithms including Hybrid Genetic Algorithm should be achieved to improve the efficiency of Genetic Algorithm for the evaluation of flatness.