• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1041-1062
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• 2015

In this paper a method of finding optimal positions for piezoelectric actuators and sensors on different structures is presented. The genetic algorithm and multi-objective genetic algorithm are selected for optimization and $H_{\infty}$ norm is defined as a cost function for the optimization process. To optimize the placement concerning the selected modes simultaneously, the multi-objective genetic algorithm is used. The optimization is investigated for two different structures: a cantilever beam and a simply supported plate. Vibrating structures are controlled in a closed loop with feedback gains, which are obtained using optimal LQ control strategy. Finally, output of a structure with optimized placement is compared with the output of the structure with an arbitrary, non-optimal placement of piezoelectric patches.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.6
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• pp.920-927
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• 1998

This paper presents a synthetic control algorithm that generates the rudder command angle to track the optimal route which is composed of straight-lines among way-points with keeping a required error limit. The control algorithm comprises three main lgorithms that is a course-keeping algorithm that eliminates the yaw angle difference between optimal route and current route a track-keeping algorithm that tracks the optimal route among way-points and a turning-control algorithm that includes the generation of optimal turning routes and control method. The effectiveness of the proposed control algorithm is assured through computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.61-61
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• 2000

Since FMS(Flexible Manufacturing System) such as semiconductor production systems have the characteristic that each device has to be commonly used in several stages, it is difficult to find an optimal solution. In this paper, we proposed the new algorithm which can get the optimal ratio of sharing resources. We will implement the proposed algorithm to semiconductor production systems. We introduce the optimal algorithm, which is modeled and analyzed by ExSpect, a petri net based simulation tool. When there exist conflicts of sharing resources, the scheduling method is adopted, which gives a priority to the most preceded process. The suggested algorithm can be used not only in semiconductor production systems but also in various FMS.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.463-468
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• 2005

An experimental study on the optimal control algorithm for central heating system for minimizing energy consumption while maintaining the comfort of indoor thermal en vironment in terms of the environmental variables such as loads and weather. experimental study has been done by one using the prototype of central heating system. As a result the optimal control algorithm shows good energy performance in comparison with conventional control one.

• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.113-119
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• 2003

This paper proposes a new multiplicative inverse algorithm for the Galois field GF (2/sup m/) whose elements are represented by optimal normal basis type Ⅱ. One advantage of the normal basis is that the squaring of an element is computed by a cyclic shift of the binary representation. A normal basis element is always possible to rewrite canonical basis form. The proposed algorithm combines normal basis and canonical basis. The new algorithm is more suitable for implementation than conventional algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.156-161
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• 1997

In this thesis, based on Genetic Algorithm, a new route search algorithm is presented to search an optimal route between the origin and the destination in intelligent route guidance systems in order to minimize the route traveling time. The proposed algorithm is effectively employed to complex road networks which have diverse turn constrains, time-delay constraints due to cross signals, and stochastic traffic volume. The algorithm is also shown to significantly promote search efficiency by changing the population size of path individuals that exist in each generation through the concept of age and lifetime to each path individual. A virtual road-traffic network with various turn constraints and traffic volume is simulated, where the suggested algorithm promptly produces not only an optimal route to minimize the route cost but also the estimated travel time for any pair of the origin and the destination, while effectively avoiding turn constraints and traffic jam.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.417-420
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• 2006

This paper suggests that resource allocation algorithm in multiuser orthogonal frequncy divisioin multiplexing (OFDM). The proposed algorithm considers throughput maximization with power constraint and quality of service (QoS) constraint. This problem has a optimal solution with using well known water-filling algorithm but the algorithm requires high computational complexity. Therefore the problem needs a sub-optimal algorithm for decreasing computational complexity. We propose a sub-optimal joint subcarrier and power allocation algorithm for multiuser OFDM system and compare with previous resource allocation algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.805-809
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• 2001

This paper is presented to determine the optimal parameters of squeeze film damper using an enhanced genetic algorithm (EGA). The damper design parameters are the radius, length and radial clearance of the damper. The objective function is minimization of a transmitted load between bearing and foundation at the operating and critical speeds of a flexible rotor. The present algorithm was the synthesis of a genetic algorithm with simplex method for a local concentrate search. This hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution and can find both the global and local optimum solution. The numerical example is presented that illustrated the effectiveness of enhanced genetic algorithm for the optimal design of the squeeze film damper for reducing transmitted load.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.582-590
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits(CNC) is proposed. The analog circuits based optimal path planning is very useful since most of the optimal path planning problems require real time computation. There has already been a previous study to implement the dynamic programming with analog circuits. However, it could not be applied for the practically large size of problems since the algorithm employs the mechanism of reducing its input current/voltage by the amount of cost, which causes outputs of distant cells to become zero. In this study, a subgoal-based dynamic programming algorithm to compute the optimal path is proposed. In the algorithm, the optimal paths are computed regardless of the distance between the starting and the goal points. It finds subgoals starting from the starting point when the output of the starting cell is raised from its initial value. The subgoal is set as the next initial position to find the next subgoal until the final goal is reached. The global optimality of the proposed algorithm is discussed and two different kinds of simulations have been done for the proposed algorithm.