• Title, Summary, Keyword: algorithms

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Distributed Genetic Algorithms for the TSP (분산 유전알고리즘의 TSP 적용)

  • 박유석
    • Journal of the Korea Safety Management & Science
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    • v.3 no.3
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    • pp.191-200
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    • 2001
  • Parallel Genetic Algorithms partition the whole population into several sub-populations and search the optimal solution by exchanging the information each others periodically. Distributed Genetic Algorithm, one of Parallel Genetic Algorithms, divides a large population into several sub-populations and executes the traditional Genetic Algorithm on each sub-population independently. And periodically promising individuals selected from sub-populations are migrated by following the migration interval and migration rate to different sub-populations. In this paper, for the Travelling Salesman Problems, we analyze and compare with Distributed Genetic Algorithms using different Genetic Algorithms and using same Genetic Algorithms on each separated sub-population The simulation result shows that using different Genetic Algorithms obtains better results than using same Genetic Algorithms in Distributed Genetic Algorithms. This results look like the property of rapidly searching the approximated optima and keeping the variety of solution make interaction in different Genetic Algorithms.

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General Algorithms for Construction of Broadcast and Multicast Trees with Applications to Wireless Networks

  • Nguyen Gam D.
    • Journal of Communications and Networks
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    • v.7 no.3
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    • pp.263-277
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    • 2005
  • In this paper, we introduce algorithms for constructing broadcasting and multicasting trees. These algorithms are general because they may be used for tree cost functions that are of arbitrary form. Thus, essentially the same algorithmic procedures are used for different tree cost functions. We evaluate the effectiveness of the general algorithms by applying them to different cost functions that are often used to model wired and wireless net­works. Besides providing a unifying framework for dealing with many present and future tree-construction applications, these algorithms typically outperform some existing algorithms that are specifically designed for energy-aware wireless networks. These general algorithms perform well at the expense of higher computational complexity. They are centralized algorithms, requiring the full network information for tree construction. Thus, we also present variations of these general algorithms to yield other algorithms that have lower complexity and distributed implementation.

Performance Analysis of a Combination of Carry-in and Remarshalling Algorithms

  • PARK, Young-Kyu;UM, Kyung-Ho
    • The Journal of Industrial Distribution & Business
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    • v.11 no.10
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    • pp.75-89
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    • 2020
  • Purpose: The container terminal is an area that plays an important role in the country's import and export. As the volume of containers increased worldwide, competition between terminals became fiercer, and increasing the productivity of terminals became more important. Re-handling is a serious obstacle that lowers the productivity of terminal. There are two ways to reduce re-handling in the terminal yard. The first method is to load containers in terminal yards using effective carry-in algorithms that reduce re-handling. The second method is to carry out effective remarshalling. In this paper, the performance of various carry-in algorithms and various remarshalling algorithms are reviewed. Next, we try to find the most effective combination of carry-in algorithm and remarshalling algorithm. Research design, data and methodology: In this paper, we analyze the performance of the four carry-in algorithms, AP, MDF, LVF, RP and the four remarshalling algorithms, ASI, ASI+, ASO, ASO+. And after making all the combinations of carry-in algorithms and remarshalling algorithms, we compare their performance to find the best combination. To that end, many experiments are conducted with eight types of 100 bays through simulation. Results: The results of experiments showed that AP was effective among the carry-in algorithms and ASO+ was effective among remarshalling algorithms. In the case of the LVF algorithm, the effect of carrying in was bad, but it was found to be effective in finding remarshalling solution. And we could see that ASI+ and ASO+, algorithms that carry out remarshalling even if they fail to find remarshalling solution, are also more effective than ASI and ASO. And among the combinations of carry-in algorithms and remarshalling algorithms, we could see that the combination of AP algorithm and ASO+ algorithm was the most effective combination. Conclusion: We compared the performance of the carry-in algorithms and the remarshalling algorithms and the performance of their combination. Since the performance of the container yard has a significant effect on the performance of the entire container terminal, it is believed that the results of this experiment will be effective in improving the performance of the container terminal when carrying-in or when remarshalling.

New conter location algorithms for shared multicast trees (공유된 멀티캐스트 트리에서 센터 위치 결정을 위한 새 알고리즘)

  • 강신규;심영철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.3B
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    • pp.493-503
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    • 2000
  • Multicast routing algorithms such PIM, CBT, BGMP use shared multicast routing trees and the location of the multicast tree has great impact on the packet delay. In this pater we propose three new center location algorithms and analyze their performance through simulation studies. these three algorithms consider as candidates for the center not only multicast group members but also a few non-members nodes. To select these non-member nodes, we first find all the shortest paths among every couple of members and consider either nodes which are most frequently visited during the process of finding shortest paths or nodes which lie at the center of a shortest path and are most frequently visited during the same process. There the proposed algorithms are able to find the better center than not only algorithms which consider only member nodes but also other algorithms which consider selected non-member nodes in addition ot member nodes. The proposed algorithms either incur too much overhead nor depend upon unicasting algorithms.

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Discrete Optimum Design of Space Truss Structures Using Genetic Algorithms

  • Park, Choon Wook;Kang, Moon Myung
    • Architectural research
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    • v.4 no.1
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    • pp.33-38
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    • 2002
  • The objective of this study is the development of discrete optimum design algorithms which is based on the genetic algorithms. The developed algorithms was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses structures and the constraints are stresses and displacements. This study solves the problem by introducing the genetic algorithms. The genetic algorithms consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed discrete optimum design algorithms was verified by applying the algorithms to optimum design examples.

New Bandwidth Guaranteed Routing Algorithms based on K-Shortest Path Algorithm (K-Shortest Path 알고리즘에 기초한 새로운 대역폭 보장 라우팅 알고리즘)

  • 이준호;이성호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.11B
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    • pp.972-984
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    • 2003
  • In this paper, new on-line routing algorithms with a bandwidth constraint are proposed. The proposed algorithms may be used for a dynamic LSP setup in MPLS network. We extend the WSP algorithm, the SWP algorithm and a utilization-based routing algorithm into the proposed algorithms by slightly modified K-shortest loopless path algorithms. The performances such as accepted bandwidth, accepted request number and average path length of the proposed and the previous algorithms are evaluated through extensive simulations. All simulations are conducted under the condition that any node can be an ingress or egress node for a LSP setup. The simulation results show that the proposed algorithms have the good performances in most cases in comparison to the previous algorithms. Under the heavy load condition, the algorithms based on the minimum hop path perform better than any other algorithms.

A Computationally Efficient Optimal Allocation Algorithms for Large Data

  • Kwon, Il-Hyung;Kim, Ju-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.561-572
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    • 2007
  • In this paper, we describe various efficient optimization algorithms for obtaining an optimal customer allocation in the telephone call center. The main advantages of the proposed algorithms are simple, fast and very attractive for massive dataset. The proposed algorithms also provide comparable performance with the other more sophisticated linear programming methods. The proposed optimal allocation algorithms increase the customer contact, response rate and management product and optimize the performance of call centers. Simulation results are given to demonstrate the effectiveness of our algorithms.

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Comparison of Binary Discretization Algorithms for Data Mining

  • Na, Jong-Hwa;Kim, Jeong-Mi;Cho, Wan-Sup
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.769-780
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    • 2005
  • Recently, the discretization algorithms for continuous data have been actively studied. But there are few articles to compare the efficiency of these algorithms. In this paper we introduce the principles of some binary discretization algorithms including C4.5, CART and QUEST and investigate the efficiency of these algorithms through numerical study. For various underlying distribution, we compare these algorithms in view of misclassification rate and MSE. Real data examples are also included.

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A Comparison Study of Classification Algorithms in Data Mining

  • Lee, Seung-Joo;Jun, Sung-Rae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.1
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    • pp.1-5
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    • 2008
  • Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

Competitive Generation for Genetic Algorithms

  • Jung, Sung-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.86-93
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    • 2007
  • A new operation termed competitive generation in the processes of genetic algorithms is proposed for accelerating the optimization speed of genetic algorithms. The competitive generation devised by considering the competition of sperms for fertilization provides a good opportunity for the genetic algorithms to approach global optimum without falling into local optimum. Experimental results with typical problems showed that the genetic algorithms with competitive generation are superior to those without the competitive generation.