• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.29 no.1
• /
• pp.109-115
• /
• 2006

Exact solutions for practical-size problems in job shop will be highly inefficient. Scheduling heuristics, therefore, are typically found in the literature. If we consider real-life situations such as machine breakdowns, the existing scheduling methods will be even more limited. Scheduling against due-dates addresses one of the most critical issues in modern manufacturing systems. In this paper, the method for weighted tardiness schedule using a graph theoretic decomposition heuristic is presented. It outstands the efficiency of computation as well as the robustness of the schedule.

• Journal of the Ergonomics Society of Korea
• /
• v.7 no.1
• /
• pp.31-37
• /
• 1988

This paper designs, in the teleoperation task, the world coordinate system by the functional analysis of each of the robot joint so that the human operator performs easily the task. Also, it constructs the heuristic rules of the equal motion line coordinates for the position and the posture control of the robot within the knowledge base so that the robot hand reaches-possibly in any position of the robot's work space. As shown in the result of the experiments. the coordinate reading is easy because the work station is displayed to the high resolution by using the superimposer of the motion analysing computer system. Also. the task burden of the human operator reduces and the error recovery time reduces because the coordinates of the object is obtained just by touch using the digitizer.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.12
• /
• pp.589-594
• /
• 2000

The fuzzy controllers have been applied to the power system stabilizer due to its excellent properties on the nonlinear systems. But the design process of fuzzy controller requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This process is time consuming task. This paper presents an parameters tuning method of the fuzzy power system stabilizer using the genetic algorithm and simulated annealing(SA). The proposed method searches the local minimum point using the simulated annealing algorithm. The proposed method is applied to the one-machine infinite-bus of a power system. Through the comparative simulation with conventional stabilizer and fuzzy stabilizer tuned by genetic algorithm under various operating conditions and system parameters, the robustness of fuzzy stabilizer tuned by proposed method with respect to the nonlinear power system is verified.

• Industrial Engineering and Management Systems
• /
• v.15 no.1
• /
• pp.32-40
• /
• 2016

This paper considers a special case of a three machine flow shop scheduling problem in which operation processing time of each job is ordered such that machine 1 has the longest processing time, whereas machine 3, the shortest processing time. The objective of the problem is the minimization of the total completion time. Although the problem is simple, its complexity is yet to be established to our best knowledge. This paper first introduces the problem and presents some optimal properties of the problem. Then, it establishes several special cases in which a polynomial-time optimal solution procedure can be found. In addition, the paper proves that the recognition version of the problem is at least binary NP-complete. The complexity of the problem has been open despite its simple structure and this paper finally establishes its complexity. Finally, a simple and intuitive heuristic is developed and the tight worst case bound on relative error of 6/5 is established.

• Proceedings of the KIEE Conference
• /
• 2002.06a
• /
• pp.41-45
• /
• 2002

In industrial computer vision systems, the image quality is dependent on the parameters such as light source, illumination method, optics, and surface properties. Most of them are related with the lighting system, which is designed in heuristic, based on the designer's experimental knowledge, In this paper, a design code by which the optimal lighting method and light source for computer vision systems can be found are suggested based on experimental results, To prove the usefulness of the design code, it is applied to the lighting system design of the transistor marking inspection system and the results are presented.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.6
• /
• pp.767-772
• /
• 2018

Recently, some meta-heuristic algorithms, such as GA(Genetic Algorithm) and GP(Genetic Programming), have been used to optimize CNN(Convolutional Neural Network). The CNN, which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures still requires expert knowledge and a lot of trial and error. In this paper, the recent attempts to automatically construct CNN architectures are investigated and analyzed. First, two GA based methods are summarized. One is the optimization of CNN structures with the number and size of filters, connection between consecutive layers, and activation functions of each layer. The other is an new encoding method to represent complex convolutional layers in a fixed-length binary string, Second, CGP(Cartesian Genetic Programming) based method is surveyed for CNN structure optimization with highly functional modules, such as convolutional blocks and tensor concatenation, as the node functions in CGP. The comparison for three approaches is analysed and the outlook for the potential next steps is suggested.

• Proceedings of the KIEE Conference
• /
• 1998.11a
• /
• pp.326-328
• /
• 1998

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. The fuzzy logic controllers has been applied to a power system stabilizing controllers. But the design of a fuzzy logic power system stabilizer relies on empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents the optimal design method of the fuzzy logic stabilizer using the genetic algorithm, which is the optimization method based on the mechanics of natural selection and natural genetics. The proposed method tunes the parameters of the fuzzy logic stabilizer in order to minimize the consuming time during the design process. In this paper, the proposed method tunes the shape of membership function of the fuzzy variables. The proposed system is applied to the one-machine infinite-bus model of a power system. Through the case study, the efficiency of the fuzzy stabilizing controller tuned by genetic algorithm is verified.

• Journal of Biomedical Engineering Research
• /
• v.14 no.2
• /
• pp.185-193
• /
• 1993

In this paper, the peak detection algorithm was developed for the purpose of screening of the target compounds. Algorithm is divided into searching the characteristic ion and peak detection. The heuristic knowledge about analytical chemistry was applied for the searching the characteristic ion. Peak detection was accomplished in comparison with the peak identification strings and pattern strings around the retention time. Pattern strings are composed with the number which generated by pattern identification function. The variables of pattern identification function are the codes which represent the difference of two adjacent abundances Some of the free steroids were selected to demonstrate the proposed algorithm.

• 한국IT서비스학회:학술대회논문집
• /
• 2006.11a
• /
• pp.593-599
• /
• 2006

Including technical device and general information system, the information-technical(IT) system is defined as the technical system for acquiring, processing, storing and transferring information to a person. This paper presents Knowledge-based Heuristic Evolution Model for creating the advanced information-technical system. This Evolution Model is derived from the historical review on definition of evolution, the research on the architecture of the general IT system, history of IT system, technology innovation theory and multi-case study research. The evolution model is applicable to the conceptual creation of the advanced product in R&D organization requiring development methodologies like rapid-prototyping to develop next generation product. For the detailed theoretical construction and practical application of Evolution Model, the case study research based on action research is performed. the object of the case study is mobile device, especially mobile hand-held phone. Thus, we obtain the Evolution Model for creating the advanced information-technical system.

• The KIPS Transactions:PartB
• /
• v.10B no.3
• /
• pp.281-286
• /
• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.