• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.99-104
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• 2002

This paper presents a method of sensitivity analysis for the infeasible interior point method when a new variable is introduced. For the sensitivity analysis in introducing a new variable, we present a method to find an optimal solution to the modified problem. If dual feasibility is satisfied, the optimal solution to the modified problem is the same as that of the original problem. If dual feasibility is not satisfied, we first check whether the optimal solution to the modified problem can be easily obtained by moving only dual solution to the original problem. If it is possible, the optimal solution to the modified problem is obtained by simple modification of the optimal solution to the original problem. Otherwise, a method to set an initial solution for the infeasible interior point method is presented to reduce the number of iterations required. The experimental results are presented to demonstrate that the proposed method works better.

• Bulletin of the Korean Mathematical Society
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• v.53 no.6
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• pp.1831-1844
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• 2016

In this paper, we improve the full-Newton step infeasible interior-point algorithm proposed by Mansouri et al. [6]. The algorithm takes only one full-Newton step in a major iteration. To perform this step, the algorithm adopts the largest logical value for the barrier update parameter ${\theta}$. This value is adapted with the value of proximity function ${\delta}$ related to (x, y, s) in current iteration of the algorithm. We derive a suitable interval to change the parameter ${\theta}$ from iteration to iteration. This leads to more flexibilities in the algorithm, compared to the situation that ${\theta}$ takes a default fixed value.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.3-11
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• 1993

We propose a new dual simplex method using a primal interior point. The dropping variable is chosen by utilizing the primal feasible interior point. For a given dual feasible basis, its corresponding primal infeasible basic vector and the interior point are used for obtaining a decreasing primal feasible point The computation time of moving on interior point in our method takes much less than that od Karmarker-type interior methods. Since any polynomial time interior methods can be applied to our method we conjectured that a slight modification of our method can give a polynomial time complexity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.285-288
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• 1996

Generally MPS, standardized by IBM, is the input type of large scale linear programming problems, and there may be unnecessary variables or constraints. These can be discarded by preprocessing. As the size of a problem is reduced by preprocessing, the running time is reduced. And more, the infeasibility of a problem may be detected before using solution methods. When the preprocessing implemented by this paper is used in NETLIB problems, it removes unnecessary variables and constraints by 21%, 15%, respectively. The use of preprocessing gives in the average 21% reduction in running time by applying the interior point method. Preprocessing can detect 10 out of 30 infeasible NETLIB problems.