• Title/Summary/Keyword: Combinatorial method

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Automatic Local Update of Triangular Mesh Models Based on Measurement Point Clouds (측정된 점데이터 기반 삼각형망 곡면 메쉬 모델의 국부적 자동 수정)

  • Woo, Hyuck-Je;Lee, Jong-Dae;Lee, Kwan-H.
    • Korean Journal of Computational Design and Engineering
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    • v.11 no.5
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    • pp.335-343
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    • 2006
  • Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

Improvement of the Reliability Graph with General Gates to Analyze the Reliability of Dynamic Systems That Have Various Operation Modes

  • Shin, Seung Ki;No, Young Gyu;Seong, Poong Hyun
    • Nuclear Engineering and Technology
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    • v.48 no.2
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    • pp.386-403
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    • 2016
  • The safety of nuclear power plants is analyzed by a probabilistic risk assessment, and the fault tree analysis is the most widely used method for a risk assessment with the event tree analysis. One of the well-known disadvantages of the fault tree is that drawing a fault tree for a complex system is a very cumbersome task. Thus, several graphical modeling methods have been proposed for the convenient and intuitive modeling of complex systems. In this paper, the reliability graph with general gates (RGGG) method, one of the intuitive graphical modeling methods based on Bayesian networks, is improved for the reliability analyses of dynamic systems that have various operation modes with time. A reliability matrix is proposed and it is explained how to utilize the reliability matrix in the RGGG for various cases of operation mode changes. The proposed RGGG with a reliability matrix provides a convenient and intuitive modeling of various operation modes of complex systems, and can also be utilized with dynamic nodes that analyze the failure sequences of subcomponents. The combinatorial use of a reliability matrix with dynamic nodes is illustrated through an application to a shutdown cooling system in a nuclear power plant.

SIMULATED ANNEALING FOR LINEAR SCHEDULING PROJECTS WITH MULTIPLE RESOURCE CONSTRAINTS

  • C.I. Yen
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.530-539
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    • 2007
  • Many construction projects such as highways, pipelines, tunnels, and high-rise buildings typically contain repetitive activities. Research has shown that the Critical Path Method (CPM) is not efficient in scheduling linear construction projects that involve repetitive tasks. Linear Scheduling Method (LSM) is one of the techniques that have been developed since 1960s to handle projects with repetitive characteristics. Although LSM has been regarded as a technique that provides significant advantages over CPM in linear construction projects, it has been mainly viewed as a graphical complement to the CPM. Studies of scheduling linear construction projects with resource consideration are rare, especially with multiple resource constraints. The objective of this proposed research is to explore a resource assignment mechanism, which assigns multiple critical resources to all activities to minimize the project duration while satisfying the activities precedence relationship and resource limitations. Resources assigned to an activity are allowed to vary within a range at different stations, which is a combinatorial optimization problem in nature. A heuristic multiple resource allocation algorithm is explored to obtain a feasible initial solution. The Simulated Annealing search algorithm is then utilized to improve the initial solution for obtaining near-optimum solutions. A housing example is studied to demonstrate the resource assignment mechanism.

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A Combined Greedy Neighbor Generation Method of Local Search for the Traveling Salesman Problem

  • Yongho Kim;Junha Hwang
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.4
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    • pp.1-8
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    • 2024
  • The traveling salesman problem(TSP) is one of the well known combinatorial optimization problems. Local search has been used as a method to solve TSP. Greedy Random Insertion(GRI) is known as an effective neighbor generation method for local search. GRI selects some cities from the current solution randomly and inserts them one by one into the best position of the current partial solution considering only one city at a time. We first propose another greedy neighbor generation method which is named Full Greedy Insertion(FGI). FGI determines insertion location one by one like GRI, but considers all remaining cities at once. And then we propose a method to combine GRI with FGI, in which GRI or FGI is randomly selected and executed at each iteration in simulated annealing. According to the experimental results, FGI alone does not necessarily perform very well. However, we confirmed that the combined method outperforms the existing local search methods including GRI.

Multiobjective Genetic Algorithm for Design of an Bicriteria Network Topology (이중구속 통신망 설계를 위한 다목적 유전 알고리즘)

  • Kim, Dong-Il;Kwon, Key-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.39 no.4
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    • pp.10-18
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    • 2002
  • Network topology design is a multiobjective problem with various design components. The components such as cost, message delay and reliability are important to gain the best performance. Recently, Genetic Algorithms(GAs) have been widely used as an optimization method for real-world problems such as combinatorial optimization, network topology design, and so on. This paper proposed a method of Multi-objective GA for Design of the network topology which is to minimize connection cost and message delay time. A common difficulty in multiobjective optimization is the existence of an objective conflict. We used the prufer number and cluster string for encoding, parato elimination method and niche-formation method for the fitness sharing method, and reformation elitism for the prevention of pre-convergence. From the simulation, the proposed method shows that the better candidates of network architecture can be found.

Region Segmentation from MR Brain Image Using an Ant Colony Optimization Algorithm (개미 군집 최적화 알고리즘을 이용한 뇌 자기공명 영상의 영역분할)

  • Lee, Myung-Eun;Kim, Soo-Hyung;Lim, Jun-Sik
    • The KIPS Transactions:PartB
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    • v.16B no.3
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    • pp.195-202
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    • 2009
  • In this paper, we propose the regions segmentation method of the white matter and the gray matter for brain MR image by using the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. This algorithm finds the expected pixel for image as the real ant finds the food from nest to food source. Then ants deposit pheromone on the pixels, and the pheromone will affect the motion of next ants. At each iteration step, ants will change their positions in the image according to the transition rule. Finally, we can obtain the segmentation results through analyzing the pheromone distribution in the image. We compared the proposed method with other threshold methods, viz. the Otsu' method, the genetic algorithm, the fuzzy method, and the original ant colony optimization algorithm. From comparison results, the proposed method is more exact than other threshold methods for the segmentation of specific region structures in MR brain image.

Synthesis and Screening of the System $SrO-Gd_2O_3-Al_2O_3$Doped with Tb by Polymerized-Complex Combinatorial Chemistry (고분자 착체 조합 화학법을 이용한 Tb이 첨가된 $SrO-Gd_2O_3-Al_2O_3$계 형광물질의 합성 및 탐색)

  • Jeong, Yang Sun;Kim, Chang Hae;Park, Hee Dong;Park, Joon Taik;Kang, Sung Kwon
    • Journal of the Korean Chemical Society
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    • v.45 no.5
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    • pp.461-469
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    • 2001
  • The combinatorial approach has been applied to discover and optimize the composition of the novel or enhanced materials. In this study, we screened the optimum composition of the system SrO-Gd$_2$O$_3$-Al$_2$O$_3$ doped with $Tb^{3+}$ by a polymerized-complex combinatorial chemistry method. Mixtures with compositions of Sr, Gd and Al component that is in the range from 0 to 1 in about 0.05 increments could be tested. The sample powders were synthesized by a polymerized complex method. To prepare appropriately polymeric precursors, we used the metallic nitrates, citric acid and ethylene glycol. The luminescence properties of the synthesized powders are investigated using the UV and VUV (Vacuum-UV: 147 nm) photoluminescence spectrometer. In addition, the crystallinity and morphology of powder were monitored by X-ray diffraction spectrometer and scanning electron microscopy. In result of VUV PL works, there are good luminescent samples with the composition of 0.595 < x < 0.733 and 0.016 < y < 0.017 in Gd1-x-yAlxTbyO$\delta$ and 0.049 < x < 0.064 and 0.02 < y < 0.039 in $Sr_xAl_{1-x-y}Tb_yO_$\delta$$, their materials can be applicable to plasma display panels as the green phosphor.

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Development of Bridge Management System for Next Generation based on Life-Cycle Cost and Performance (생애주기 비용 및 성능을 고려한 차세대 교량 유지관리기법 개발)

  • Park, Kyung-Hoon
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2007.11a
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    • pp.167-174
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    • 2007
  • This study proposes a practical and realistic method to establish an optimal lifetime maintenance strategy for deteriorating bridges by considering the life-cycle performance as well as the life-cycle cost. The proposed method offers a set of optimal tradeoff maintenance scenarios among other conflicting objectives, such as minimizing cost and maximizing performance. A genetic algorithm is used to generate a set of maintenance scenarios that is a multi-objective combinatorial optimization problem related to the and the life-cycle cost and performance as separate objective functions. A computer program, which generates optimal maintenance scenarios, was developed based on the proposed method. The subordinate relation between bridge members has been considered to decide optimal maintenance sequence. The developed program has been used to present a procedure for finding an optimal maintenance scenario for steel-girder bridges on the Korean National Road. Through this bridge maintenance scenario analysis, it is expected that the developed method and program can be effectively used to allow bridge managers an optimal maintenance strategy satisfying various constraints and requirements.

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Statistical methods for testing tumor heterogeneity (종양 이질성을 검정을 위한 통계적 방법론 연구)

  • Lee, Dong Neuck;Lim, Changwon
    • The Korean Journal of Applied Statistics
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    • v.32 no.3
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    • pp.331-348
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    • 2019
  • Understanding the tumor heterogeneity due to differences in the growth pattern of metastatic tumors and rate of change is important for understanding the sensitivity of tumor cells to drugs and finding appropriate therapies. It is often possible to test for differences in population means using t-test or ANOVA when the group of N samples is distinct. However, these statistical methods can not be used unless the groups are distinguished as the data covered in this paper. Statistical methods have been studied to test heterogeneity between samples. The minimum combination t-test method is one of them. In this paper, we propose a maximum combinatorial t-test method that takes into account combinations that bisect data at different ratios. Also we propose a method based on the idea that examining the heterogeneity of a sample is equivalent to testing whether the number of optimal clusters is one in the cluster analysis. We verified that the proposed methods, maximum combination t-test method and gap statistic, have better type-I error and power than the previously proposed method based on simulation study and obtained the results through real data analysis.

Development of Bridge Maintenance Method based on Life-Cycle Performance and Cost (생애주기 성능 및 비용에 기초한 교량 유지관리기법 개발)

  • Park, Kyung Hoon;Kong, Jung Sik;Hwang, Yoon Koog;Cho, Hyo Nam
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6A
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    • pp.1023-1032
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    • 2006
  • In this paper, a new method for the bridge maintenance is proposed to overcome the limit of the existing methods and to implement the preventive bridge maintenance system. The proposed method can establish the lifetime optimum maintenance strategy of the deteriorating bridges considering the life-cycle performance as well as the life-cycle cost. The lifetime performance of the deteriorating bridges is evaluated by the safety index based on the structural reliability and the condition index detailing the condition state. The life-cycle cost is estimated by considering not only the direct maintenance cost but also the user and failure cost. The genetic algorithm is applied to generate a set of maintenance scenarios which is the multi-objective combinatorial optimization problem related to the life-cycle cost and performance. The study examined the proposed method by establishing a maintenance strategy for the existing bridge and its advantages. The result shows that the proposed method can be effectively applied to deciding the bridge maintenance strategy.