• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.202-210
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• 1995

Given a tree T with a root node 0 having the capacity H and a profit $c_{v}$ and a demand $d_{v}$ on each node v of T, the capacitated subtree of a tree problem(CSTP) is to find a subtree of T containing the root that has the maximum total profit, the sum of profits over the subtree, and also satisfies the constraint of which the sum of demands over the subtree must be less than or equal to H. We first define the so-called critical item for CSTP and find an upper bound on the linear programming relaxation of CSTP. We then present our branch and bound algorithm for solving CSTP and finally report the computational results on a set of randomly generated test problems.s.s.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.312-315
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• 2006

Overlay Multicast is a promising approach to overcome the implementation problem of IP multicast. Real time services like internet broadcasting are provided by overlay multicast technology due to the complex nature of IP multicast and the high cost to support multicast function. Since multicast members can dynamically join or leave their multicast group, it is necessary to keep a reliable overlay multicast tree to support real time service without delay. In this paper, we consider path level reliability that connects each member node. The problem is formulated as a binary integer programming which maximizes the reliability of multicast tree. Tabu search based algorithm is presented to solve the NP-hard problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1056-1064
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• 2003

The Euclidean steiner tree problem (ESTP) is to find a minimum-length euclidean interconnection of a set of points in the plane. It is well known that the solution to this problem will be the minimal spanning tree (MST) on some set steiner points, and the ESTP is NP-complete. The ESTP has received a lot of attention in the literature, and heuristic and optimal algorithms have been proposed. In real field, heuristic algorithms for ESTP are popular. A key performance measure of the algorithm for the ESTP is the reduction rate that is achieved by the difference between the objective value of the ESTP and that of the MST without steiner points. In recent survey for ESTP, the best heuristic algorithm showed around $3.14\%$ reduction in the performance measure. We present a evolution programming (EP) for ESTP based upon the Prim algorithm for the MST problem. The computational results show that the EP can generate better results than already known heuristic algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• Health Policy and Management
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• v.12 no.3
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• pp.99-111
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• 2002

This paper draws the determinants of National Health Expenditures(min) and collectivizes OECD countries which are positioned by same conditions using the decision tree analysis. Major findings are summarized as follows. We find that the power of influence of income level on NHE has been 58.35% in 1985, 65.37% in 1990, 66.90% in 1995, and 66.47% in 1997. The power of influence of public share in NHE has been on the increase during that period: 19.50% in 1985, 19.91% in 1990, 22.81% in 1995 and 26.88% in 1997. The two factors(income level, public share) tells for the most part of NHE: 77.85% in 1985, 85.28% in 1990, 89.71% in 1995, 93.35% in 1997. Our results support the hypothesis that NHE could be explained mostly by the income level and show that public share is negatively correlated with the growth of NHE.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.23-30
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• 2002

본 연구는 추가제약이 있는 최소 신장나무 문제(Constrained Minimum Spanning Tree : CMST문제)에 대한 유사다항시간 알고리듬 및 근사 해법 개발에 관한 것이다. CMST문제는 NP-hard문제임이 이미 증명되었으며, 이후 이 문제에 대해서는 근사해법 개발이 주된 관심이 되어왔다 [Ravi and Goemans 96]는 다항시간 근사 해법(PTAS)을 이미 개발하였고, [Marathe et at 98]은 가능해(feasible solution)는 아니지만, 앞으로 서술할 $(1+1/\varepsilon,\;+\epsilon)$사해를 구하는 완전다항시간 근사해법 (FPTAS)을 제시하였다. 이와는 달리 [Papa. and Yan, 00]는 파레토 근사 최적해를 구하는 FPTAS를 제시하였는데, 본 연구는 이들의 연구에서 주로 의존하고 있는 행렬-나무 정리(Tree-Matrix Theorem)를 보다 일반화하여, CMST문제에 대한 유사다항시간 알고리듬과 $(1+\varepsilon,\;1+\epsilon)$근사해를 구하는 FPTAS를 제시할 것이다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.402-408
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• 2002

Multicast technology allows the transmission of data from one source node to a selected group of destination nodes. Multicast routes typically use trees, called multicast routing trees, to minimize resource usage such as cost and bandwidth by sharing links. Moreover, the quality of service (QoS) is satisfied by distributing data along a path haying no more than a given number of arcs between the root node of a session and a terminal node of it in the routing tree. Thus, a multicast routing tree for a session can be represented as a hop constrained Steiner tree. In this paper, we consider the hop-constrained multicast route packing problem with bandwidth reservation. Given a set of multicast sessions, each of which has a hop limit constraint and a required bandwidth, the problem is to determine a set of multicast routing trees in an arc-capacitated network to minimize cost. We propose an integer programming formulation of the problem and an algorithm to solve it. An efficient column generation technique to solve the linear programming relaxation is proposed, and a modified cover inequality is used to strengthen the integer programming formulation.

• Journal of the Korea Safety Management & Science
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• v.17 no.2
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• pp.241-247
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• 2015

The purpose of the warranty data analysis can be classified into two categories. Two goals is a failure cause analysis and life prediction analysis. In this paper first, we applied multivariate analysis method that can be estimated in consideration of various factors on the failure cause warranty data. In particular, we apply the Tree model and Cox model. The advantage of the Tree is easy to interpret this result as compared to other models. In addition Cox model can quantitatively express the risk. Second, this paper proposed a multivariate life prediction model (AFT) considering a variety of factors. By applying the actual warranty data confirmed the usability.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.1-11
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• 2023

Clustering analysis is used in various fields including customer segmentation and clustering methods such as k-means are actively applied in the credit card customer segmentation. In this paper, we summarized the input features selection method of k-means clustering for the case of the credit card customer segmentation problem, and evaluated its feasibility through the analysis results. By using the label values of k-means clustering results as target features of a decision tree classification, we composed a method for prioritizing input features using the information gain of the branch. It is not easy to determine effectiveness with the clustering effectiveness index, but in the case of the CH index, cluster effectiveness is improved evidently in the method presented in this paper compared to the case of randomly determining priorities. The suggested method can be used for effectiveness of actively used clustering analysis including k-means method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.2
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• pp.1-10
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• 2024

For the purpose of predicting credit card customer churn accurately through data analysis, a model can be constructed with various machine learning algorithms, including decision tree. And feature importance has been utilized in selecting better input features that can improve performance of data analysis models for several application areas. In this paper, a method of utilizing feature importance calculated from the MDI method and its effects are investigated in the credit card customer churn prediction problem with classification trees. Compared with several random feature selections from case data, a set of input features selected from higher value of feature importance shows higher predictive power. It can be an efficient method for classifying and choosing input features necessary for improving prediction performance. The method organized in this paper can be an alternative to the selection of input features using feature importance in composing and using classification trees, including credit card customer churn prediction.