• 제목/요약/키워드: optimal algorithm

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A QoS Multicast Routing Optimization Algorithm Based on Genetic Algorithm

  • Sun Baolin;Li Layuan
    • Journal of Communications and Networks
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    • 제8권1호
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    • pp.116-122
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    • 2006
  • Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

A Path Generation Algorithm of Autonomous Robot Vehicle By the Sensor Platform and Optimal Controller Based On the Kinematic Model

  • Park, Tong-Jin;Han, Chang-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.399-399
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    • 2000
  • In this paper, path generation using the sensor platform is proposed. The sensor platform is composed two electric motors which make panning and tilting motions. An algorithm fur a real path form and an obstacle length is realized using a scanning algorithm to rotating the sensors on the sensor platform. An ARV (Autonomous Robot Vehicle) is able to recognize the given path by adapting this algorithm. In order for the ARV to navigate the path flexibly, a kinematic model needed to be constructed. The kinematic model of the ARV was reformed around its body center through a relative velocity relationship to controllability, which derives from the nonholonomic characteristics. The optimal controller that is based on tile kinematic model is operated purposefully to track a reference vehicle's path. The path generation algorithm is composed of two parks. On e part is the generating path pattern, and the other is used to avoid an obstacle. The optimal controller is used for tracking the reference path which is generated by recognizing the path pattern. Results of simulation show that this algorithm for an ARV is sufficient for path generation by small number of sensors and for low cost controller.

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k-opt를 적용한 차수 제약 최소신장트리 알고리즘 (A Degree-Constrained Minimum Spanning Tree Algorithm Using k-opt)

  • 이상운
    • 한국컴퓨터정보학회논문지
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    • 제20권5호
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    • pp.31-39
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    • 2015
  • 방향 가중 그래프의 차수제약 최소신장트리 (degree-constrained minimum spanning tree, d-MST) 문제는 정확한 해를 구하는 다항시간 알고리즘이 존재하지 않아 NP-완전 문제로 알려져 왔다. 따라서 휴리스틱한 근사 알고리즘을 적용하여 최적 해를 구하고 있다. 본 논문은 차수와 사이클을 검증하는 Kruskal 알고리즘으로 d-MST의 초기 해를 구하고, d-MST의 초기 해에 대해 k-opt를 수행하여 최적 해를 구하는 다항시간 알고리즘을 제안하였다. 제안된 알고리즘을 4개의 그래프에 적용한 결과 2-MST까지 최적 해를 구할 수 있었다.

Continuous size optimization of large-scale dome structures with dynamic constraints

  • Dede, Tayfun;Grzywinski, Maksym;Selejdak, Jacek
    • Structural Engineering and Mechanics
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    • 제73권4호
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    • pp.397-405
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    • 2020
  • In this study size optimization of large-scale dome structures with dynamic constraints is presented. In the optimal design of these structure, the Jaya algorithm is used to find minimal size of design variables. The design variables are the cross-sectional areas of the steel truss bar elements. To take into account the constraints which are the first five natural frequencies of the structures, the finite element analysis is coded in Matlab programs using eigen values of the stiffness matrix of the dome structures. The Jaya algorithm and the finite elements codes are combined by the help of the Matlab - GUI (Graphical User Interface) programming to carry out the optimization process for the dome structures. To show the efficiency and the advances of the Jaya algorithm, 1180 bar dome structure and the 1410 bar dome structure were tested by taking into the frequency constraints. The optimal results obtained by the proposed algorithm are compared with those given in the literature to demonstrate the performance of the Jaya algorithm. At the end of the study, it is concluded that the proposed algorithm can be effectively used in the optimal design of large-scale dome structures.

무기 목표물 배정 문제의 최대 치사인원 선택 알고리즘 (Maximum Kill Selection Algorithm for Weapon Target Assignment (WTA) Problem)

  • 이상운
    • 한국인터넷방송통신학회논문지
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    • 제19권2호
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    • pp.221-227
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    • 2019
  • 무기 목표물 배정 문제는 지금까지 다항시간 알고리즘이 제안되지 않는 NP-hard 문제로 알려져 왔다. 그럼에도 불구하고, 본 문제에 대해 가능한 모든 경우수를 검증하는 Brute-Force 법이나 분기한정법으로 최적 해를 구하거나 유전자 알고리즘, 입자군 최적화 등의 인공지능 방법으로 근사 해를 구하는 방법들이 제안되고 있다. 본 논문에서는 단지 무기의 총 대수 k, 무기 종류 수 m, 목표물 개수 n에 대해 O(mn)을 k회 수행하는 O(kmn) 다항시간으로 최적 해를 구하는 알고리즘을 제안하였다. 제안된 알고리즘은 Brute-Force 법에 비해 수행횟수를 최소화 시킬 뿐 아니라 최적해도 구하는 장점을 갖고 있다.

Intelligent Route Construction Algorithm for Solving Traveling Salesman Problem

  • Rahman, Md. Azizur;Islam, Ariful;Ali, Lasker Ershad
    • International Journal of Computer Science & Network Security
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    • 제21권4호
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    • pp.33-40
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    • 2021
  • The traveling salesman problem (TSP) is one of the well-known and extensively studied NPC problems in combinatorial optimization. To solve it effectively and efficiently, various optimization algorithms have been developed by scientists and researchers. However, most optimization algorithms are designed based on the concept of improving route in the iterative improvement process so that the optimal solution can be finally found. In contrast, there have been relatively few algorithms to find the optimal solution using route construction mechanism. In this paper, we propose a route construction optimization algorithm to solve the symmetric TSP with the help of ratio value. The proposed algorithm starts with a set of sub-routes consisting of three cities, and then each good sub-route is enhanced step by step on both ends until feasible routes are formed. Before each subsequent expansion, a ratio value is adopted such that the good routes are retained. The experiments are conducted on a collection of benchmark symmetric TSP datasets to evaluate the algorithm. The experimental results demonstrate that the proposed algorithm produces the best-known optimal results in some cases, and performs better than some other route construction optimization algorithms in many symmetric TSP datasets.

Multi-objective Optimization of a Laidback Fan Shaped Film-Cooling Hole Using Evolutionary Algorithm

  • Lee, Ki-Don;Husain, Afzal;Kim, Kwang-Yong
    • International Journal of Fluid Machinery and Systems
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    • 제3권2호
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    • pp.150-159
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    • 2010
  • Laidback fan shaped film-cooling hole is formulated numerically and optimized with the help of three-dimensional numerical analysis, surrogate methods, and the multi-objective evolutionary algorithm. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by four geometric design variables, the injection angle of the hole, the lateral expansion angle of the diffuser, the forward expansion angle of the hole, and the ratio of the length to the diameter of the hole, to maximize the film-cooling effectiveness compromising with the aerodynamic loss. The objective function values are numerically evaluated through Reynolds- averaged Navier-Stokes analysis at the designs that are selected through the Latin hypercube sampling method. Using these numerical simulation results, the Response Surface Approximation model are constructed for each objective function and a hybrid multi-objective evolutionary algorithm is applied to obtain the Pareto optimal front. The clustered points from Pareto optimal front were evaluated by flow analysis. These designs give enhanced objective function values in comparison with the experimental designs.

3D-EMCN법을 이용한 광 픽업 액츄에이터의 해석 및 최적설계 (Analysis and Optimal Design of Optical Pickup Actuator by 3D-EMCN Method)

  • 김진아;전태경
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제51권5호
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    • pp.234-241
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    • 2002
  • An optical pickup actuator is an objective-lens-moving mechanism that provides a means to follow the disk displacement accurately(1). In this paper, a slim type optical pickup actuator for Notebook PCs is analyzed and designed to improve the driving sensitivity A three dimensional equivalent magnetic circuit network method (3D-EMCN method) is proposed for an analysis method which provides better characteristics in both precision and computation time of analysis comparing with a commercial three-dimensional finite element (3D-FEM) codes. To verify the validity of proposed method, we made a comparison between the analysis results and the experimental ones. We also compared this analysis results with 3D-FEM results. Among the several optimal algorithm, we adopt a niching genetic algorithm, which renders a set of the multiple optimal solutions. RCS (Restricted Competition Selection) niching genetic algorithm is used for optimal design of the actuator's performance. Recently, the pickup actuator needs additional driving structure for radial and tangential tilting motion to obtain better pick-up performance. So we applied the proposed method to the model containing tilting coils.

Adaboost 최적 특징점을 이용한 차량 검출 (Vehicle Detection Using Optimal Features for Adaboost)

  • 김규영;이근후;김재호;박장식
    • 한국전자통신학회논문지
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    • 제8권8호
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    • pp.1129-1135
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    • 2013
  • 본 논문에서는 최적 특징점 선택기법를 적용한 다중 최적 Adaboost 분류기를 기반으로 새로운 차량 검출 알고리즘을 제안한다. 제안하는 알고리즘은 2 가지 주요 모듈로 구성된다. 첫 번째는 설치된 카메라의 사이트 모델링을 이용한 영상 스케일링을 기반으로 하는 이론적 DDISF(Distance Dependent Image Scaling Factor) 모듈이며, 두 번째는 차량과 카메라의 거리에 대응하는 최적 Haar-like 특징을 활용하는 것이다. 실험 결과 제안하는 알고리즘은 기존의 방법에 비하여 인식 성능이 개선됨을 확인하였다. 제안하는 알고리즘은 96.43% 의 인식률과 약 3.77%의 오검출이 발생하였다. 이러한 성능은 기존의 표준 Adabooost 알고리즘에 비하여 각각 3.69%와 1.28% 의 성능을 개선한 것이다.