• Journal of Korean Institute of Industrial Engineers
• /
• v.17 no.1
• /
• pp.75-82
• /
• 1991

This research is concerned with Machine-Part Group Formation(MPGF) methodology for Flexible Manufacturing Systems(FMS). The purpose of the research is to develop a new heuristic algorithm for effectively solving MPGF problem. The new algorithm is proposed and evaluated by 100 machine-part incidence matrices generated. The performance measures are (1) grouping ability of mutually exclusive block-diagonal form. (2) number of unit group and exceptional elements, and (3) grouping time. The new heuristic algorithm has the following characteristics to effectively conduct MPGF : (a) The mathematical model is presented for rapid forming the proper number of unit groups and grouping mutually exclusive block-diagonal form, (b) The simple and effective mathematical analysis method of Rank Order Clustering(ROC) algorithm is applied to minimize intra-group journeys in each group and exceptional elements in the whole group. The results are compared with those from Expert System(ES) algorithm and ROC algorithm. The results show that the new algorithm always gives the group of mutually exclusive block-diagonal form and better results(85%) than ES algorithm and ROC algorithm.

• Journal of information and communication convergence engineering
• /
• v.8 no.1
• /
• pp.45-50
• /
• 2010

EPCglobal Class-1 Gen-2 standard proposed Q-algorithm to select a frame size for the next query round. Q-algorithm calculates the frame size without estimating the number of tags. Therefore, the Q-algorithm has advantage that the reader's algorithm is simpler than other algorithms. However, it is impossible to allocate the optimized frame size. Also. the conventional Q-algorithm does not define an optimized parameter value C for adjusting the frame size. In this paper, we propose a modified Q-algorithm with the tag number estimation scheme, and evaluate the performance with computer simulations.

• Journal of information and communication convergence engineering
• /
• v.8 no.1
• /
• pp.23-28
• /
• 2010

According to increasing projection order, the AP algorithm bas noise amplification problem in large background noise. This phenomenon degrades the performances of the AP algorithm. In this paper, we analyze convergence characteristic of the AP algorithm and then suggest a noise robust modified AP algorithm for reducing this problem. The proposed algorithm normalizes the update equation to reduce noise amplification of AP algorithm, by adding the multiplication of error power and projection order to auto-covariance matrix of input signal. By computer simulation, we show the improved performance than conventional AP algorithm.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.4
• /
• pp.1415-1421
• /
• 2015

This paper presents a new algorithm called Quantum-behaved Electromagnetism-like Mechanism Algorithm which is used to solve economic load dispatch of power system. Electromagnetism-like mechanism algorithm simulates attraction and repulsion mechanism for particles in the electromagnetic field. Every solution is a charged particle, and it move to optimum solution according to certain criteria. Quantum-behaved electromagnetism-like mechanism algorithm merges quantum computing theory with electromagnetism-like mechanism algorithm. Superposition characteristic of quantum methodology can make a single particle present several states, and the characteristic potentially increases population diversity. Probability representation of quantum methodology is to make particle state be presented according to a certain probability. And the quantum rotation gates are used to realize update operation of particles. The algorithm is tested for 13-generator system and 40-generator system, which validates it can effectively solve economic load dispatch problem. Through performance comparison, it is obvious the solution is superior to other optimization algorithm.

• Journal of Advanced Marine Engineering and Technology
• /
• v.32 no.2
• /
• pp.351-358
• /
• 2008

This paper introduces a map building algorithm which can collect environmental information using ultrasonic sensors. And also this paper discusses a traveling algorithm using environmental information which leads to the map building algorithm. In order to accomplish the proposed traveling algorithm, this paper additionally discusses a path revision algorithm. For verifying the proposed algorithms, several experiments are executed using a mobile robot physically designed in this paper. The conclusion is that the proposed algorithm is very effective and is applicable to mobile robots especially requiring a low-cost environmental information.

• Proceedings of the KIEE Conference
• /
• 2005.05a
• /
• pp.15-17
• /
• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of nonlinear IIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate nonlinear IIR filter parameter using the genetic algorithm.

• Journal of the Korea Society for Simulation
• /
• v.3 no.1
• /
• pp.43-53
• /
• 1994

With remarkable progress of hardware technologies, multiprocessor systems equipped with thousands of processors will be available in near future. In order to increase the performance of these systems, many processor allocation algorithms have been proposed. However, few studies have been conducted in order to compare the performance of these algorithms. In this paper, simulation techniques are used in order to compare the performance of the processor allocation algorithms proved to be useful. These are: an algorithm using equipartion, an algorithm using average parallelism, an algorithm using execution signatures, and an algorithm using the number of tasks in a task precedence graph. Simulation shows that the algorithm using execution signatures performs best while the algorithm using average parallelism performs worst with small allocated processors. Surprisingly, the algorithm using equipartition performs well despite the fact that it has smallest overhead. Overall, it can be recommended that the algorithm using equipartition be used without any execution history and that the algorithm using execution signatures be used with some execution history.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.11
• /
• pp.1071-1076
• /
• 2004

It is a fuzzy controller that it is the most used method in the control of non-linear system. The most important part in the fuzzy controller is a design of fuzzy rules. Many algorithm that design fuzzy rules have proposed. And attention to the evolutionary computation is increasing in the recent days. Among them, the co-evolutionary algorithm is used in the design of optimal fuzzy rule. This paper takes advantage of a schema co-evolutionary algorithm. In order to verify the efficiency of the schema co-evolutionary algorithm, a fuzzy controller for the mobile robot control is designed by the schema co-evolutionary algorithm and it is compared with other parasitic co-evolutionary algorithm such as a virus-evolutionary genetic algorithm and a co-evolutionary method of Handa.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.502-504
• /
• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of FIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate FIR filter parameter using the genetic algorithm.

• Proceedings of the IEEK Conference
• /
• 2000.11b
• /
• pp.297-300
• /
• 2000

This paper proposes a high-speed and area-efficient FFT algorithm and performs a hardware implementation. This algorithm, named by “Radix-4/2”, uses the feature of existing radix-2$^3$algorithm, It reduces the number of non-trivial multipliers in SFG to the ratio of 3 to 2 campared with radix-2 or radix-4 algorithm and radix-4/2 has also twice throughput as radix-2$^3$algorithm's. It is proved that FFT processor using the proposed algorithm and 64-point MDC pipeline architecture has twice throughput as radix-2$^3$algorithm's, and reduces areas by 25 percentages in contrast to radix-4 algorithm's.