• The Korean Journal of Applied Statistics
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• v.5 no.1
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• pp.93-102
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• 1992

We want to derive the optimal Box-Plot Algotithm by comparing and analyzing Box-Plots used in several packages.

• Journal of Communications and Networks
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• v.8 no.1
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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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.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.31-39
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• 2015

The degree-constrained minimum spanning tree (d-MST) problem is considered NP-complete for no exact solution-yielding polynomial algorithm has been proposed to. One thus has to resort to an heuristic approximate algorithm to obtain an optimal solution to this problem. This paper therefore presents a polynomial time algorithm which obtains an intial solution to the d-MST with the help of Kruskal's algorithm and performs k-opt on the initial solution obtained so as to derive the final optimal solution. When tested on 4 graphs, the algorithm has successfully obtained the optimal solutions.

• Structural Engineering and Mechanics
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• v.73 no.4
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.221-227
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• 2019

It has long been known that weapon target assignment (WTA) problem is NP-hard. Nonetheless, an exact solution can be found using Brute-Force or branch-and bound method which utilize approximation. Many heuristic algorithms, genetic algorithm particle swarm optimization, etc., have been proposed which provide near-optimal solutions in polynomial time. This paper suggests polynomial time algorithm that can be obtain the optimal solution of WTA problem for the number of total weapons k, the number of weapon types m, and the number of targets n. This algorithm performs k times for O(mn) so the algorithm complexity is O(kmn). The proposed algorithm can be minimize the number of trials than brute-force method and can be obtain the optimal solution.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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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.

• International Journal of Fluid Machinery and Systems
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• v.3 no.2
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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.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.5
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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.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1129-1135
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• 2013

A new vehicle detection algorithm based on the multiple optimal Adaboost classifiers with optimal feature selection is proposed. It consists of two major modules: 1) Theoretical DDISF(Distance Dependent Image Scaling Factor) based image scaling by site modeling of the installed cameras. and 2) optimal features selection by Haar-like feature analysis depending on the distance of the vehicles. The experimental results of the proposed algorithm shows improved recognition rate compare to the previous methods for vehicles and non-vehicles. The proposed algorithm shows about 96.43% detection rate and about 3.77% false alarm rate. These are 3.69% and 1.28% improvement compared to the standard Adaboost algorithmt.