• Journal of computational fluids engineering
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• v.19 no.2
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• pp.72-78
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• 2014

A hybrid particle-mesh method as the combination between the Vortex-In-Cell (VIC) method and penalization method has been achieved in recent years. The VIC method, which is based on the vorticity-velocity formulation, offers particle-mesh algorithms to numerically simulate flows past a solid body. The penalization method is used to enforce boundary conditions at a body surface with a decoupling between body boundaries and computational grids. The main advantage of the hybrid particle-mesh method is an efficient implementation for solid boundaries of arbitrary complexity on Cartesian grids. However, a numerical simulation of flows in large domains is still not too easy. In this study, a multi-domain approach is thus proposed to further reduce computation cost and easily implement it. We validate the implementation by numerical simulations of an incompressible viscous flow around an impulsively started circular cylinder.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.781-787
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• 2015

This paper proposes a hybrid visual servoing algorithm for the object tracking by a mobile robot with the stereo camera. The mobile robot with the stereo camera performs an object recognition and object tracking using the SIFT and CAMSHIFT algorithms for the hybrid visual servoing. The CAMSHIFT algorithm using stereo camera images has been used to obtain the three-dimensional position and orientation of the mobile robot. With the hybrid visual servoing, a stable balance control has been realized by a control system which calculates a desired angle of the center of gravity whose location depends on variations of link rotation angles of the manipulator. A PID controller algorithm has adopted in this research for the control of the manipulator since the algorithm is simple to design and it does not require unnecessary complex dynamics. To demonstrate the control performance of the hybrid visual servoing, real experiments are performed using the mobile manipulator system developed for this research.

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.369-376
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• 2007

This paper proposes a hybrid genetic algorithm(HGA) for the classifier ensemble selection. HGA is added a local search operation for increasing the fine-turning of local area. This paper apply hybrid and simple genetic algorithms(SGA) to the classifier ensemble selection problem in order to show the superiority of HGA. And this paper propose two methods(SSO: Sequential Search Operations, CSO: Combinational Search Operations) of local search operation of hybrid genetic algorithm. Experimental results show that the HGA has better searching capability than SGA. The experiments show that the CSO considering the correlation among classifiers is better than the SSO.

• ETRI Journal
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• v.30 no.5
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• pp.653-662
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• 2008

Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti-collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation-2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti-collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.

• Korean Institute of Interior Design Journal
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• no.40
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• pp.158-164
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• 2003

The rapid development of information technology has much influence on architectural design. Collaboration beyond time and space has been possible by networking the work environment and digital products. Thus, the virtual design studio on architectural design is getting more important than ever before. This research investigates a virtual design studio methodology for effective collaboration. The building design process and the communication model are studied and possible modes of design collaboration are defined. This paper proposes an internet-based Virtual Reality(VR) communication tool as well as new design methodology that we call the 'Hybrid Design Methodology'. We expect that this design methodology will dramatically increase design feedbacks, and thus results in better design alternatives. There are two issues involved in developing the collaborative virtual design studio: 1) an intuitive interface that presents collaborative relations, and 2) three-dimensional computer-mediated communication tool using sketch as a modeling method. Further research issues identified at the end of the research include developing algorithms that translate mapping images to polygons for the drafting phase in the design process.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.802-809
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• 2005

A hybrid genetic algorithm is proposed for the problem of generating laser torch paths to cut a stock plate nested with free-formed parts each having a set of sub-parts. In the problem, the total unproductive travel distance of the torch is minimized. The problem is shown to be formulated as a special case of the standard travelling salesman problem. The hybrid genetic algorithm for solving the problem is hierarchically structured: First, it uses a genetic algorithm to find the cutting path f3r the parts and then, based on the obtained cutting path, sequence of sub-parts and their piercing locations are optimally determined by using a combined genetic and heuristic algorithms. This process is repeated until any progress in the total unproductive travel distance is not achieved. Computational results are provided to illustrate the validity of the proposed algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.357-369
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• 1995

Wafer fabrication process is the most important and critical process in semiconductor manufacturing. The process is very complicated and hard to establish an efficient schedule due to its complexity. Furthermore, several performance indices such as due dates, throughput, cycle time and workstation utilizations are to be considered simultaneously for an efficient schedule, and some of these indices have negative correlations in performances each other. We develop an efficient heuristic scheduling algorithm; Hybrid Input Control Policy and Hybrid Dispatching Rule. Through numerical experiments, it is shown that the proposed Hybrid Scheduling Algorithm gives better performance compared with existing algorithms.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.179-182
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• 2003

This paper proposes an adaptive hybrid genetic algorithm (aHGA) for effectively solving the complex reliability optimization problems. The proposed aHGA uses a loca1 search technique and an adaptive scheme for respectively constructing hybrid algorithm and adaptive ability. For more various comparisons with the proposed adaptive algorithm, other aHGAs with conventional adaptive schemes are considered. These aHGAs are tested and analyzed using two complex reliability optimization problems. Numerical result shows that the proposed aHGA outperforms the other competing aHGAs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.58-68
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• 2010

Particle Swarm Optimization (PSO) which has been well known to solve continuous problems can be applied to discrete combinatorial problems. Several DPSO (Discrete Particle Swarm Optimization) algorithms have been proposed to solve discrete problems such as traveling salesman, vehicle routing, and flow shop scheduling problems. They are different in representation of position and velocity vectors, operation mechanisms for updating vectors. In this paper, the performance of 5 DPSOs is analyzed by applying to traditional Traveling Salesman Problems. The experiment shows that DPSOs are comparable or superior to a genetic algorithm (GA). Also, hybrid PSO combined with local optimization (i.e., 2-OPT) provides much improved solutions. Since DPSO requires more computation time compared with GA, however, the performance of hybrid DPSO is not better than hybrid GA.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.76-86
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• 2002

In this paper, we suggest a hybrid genetic algorithm reinforced by a fuzzy logic controller (flc-HGA) to overcome weaknesses of conventional genetic algorithms: the problem of parameter fine-tuning, the lack of local search ability, and the convergence speed in searching process. In the proposed flc-HGA, a fuzzy logic controller is used to adaptively regulate the fine-tuning structure of genetic algorithm (GA) parameters and a local search technique is applied to find a better solution in GA loop. In numerical examples, we apply the proposed algorithm to a simple test problem and two complex combinatorial optimization problems. Experiment results show that the proposed algorithm outperforms conventional GAs and heuristics.