• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.4
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• pp.571-579
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• 1990

A dynamic relocation algorithm for non-deterministic process graph in distributed computer systems is proposed. A method is represented for determining the optimal policy for processing a process tree. A general database query request is modelled by a process tree which represent a set of subprocesses together with their precedence relationship. The process allocation model is based on operating cost which is a function fo selection of site for processing operation, data reduction function and file size. By using expected values of parameters for non-deterministic process tree, the process graph and optimal policy that yield minimum operating cost are determined. As process is relocated according to threshold value and new information of parameters after the execution of low level process for non-deterministic process graph, the assigned state that approximate to optiaml solution is obtained. The proposed algorihtm is heuristic By performing algorithm for sample problems, it is shown that the proposed algorithm is good in obtaining optimal solution.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.38-45
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• 2003

This paper presents a meta-heuristic solution technique, Ant System (AS)algerian to solve edge detection problem. We define the quality of edge in terms of dissimilarity, continuity, thickness and length. We cast edge detection as a problem in cost minimization. This is achieved by the formulation of a cost function that inversely evaluates the quality of edge configuration. Twelve windows for enhancing dissimilarity regions based on the valid edge structures are used. The AS algorithm finds the optimal set of edge pixels based on the cost function. The experimental results show that the properly reduced set of edge pixels could be found regardless how complicated the image is.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.109-121
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• 1992

In this paper, we address a layout design problem for determining a K-class-based dedicated storage layout in an automated storage retrieval system. K-class-based dedicated storage employs K zones in which lots from a class of products are stored randomly. Zones form a partition of storage locations. Our objective function is to minimize the expected single command travel time, which is expressed as a set function of space requirements for zones, average demand rates from classes, and one-way travel times from the pickup/deposit station to locations. We construct a heuristic algorithm based on analytical results and a local search method, the methodology deveolped can be used with easily-available data by warehouse planners to improve the throughput capacity of a conventional warehouse as well as an AS/RS.

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

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.314-317
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• 2010

본 연구는 차량 경로 스케줄링 문제(VRSPTW, the Vehicle Routing and Scheduling Problem with Time Window)를 해결하기 위하여, 멀티 비용 함수(Multi Cost Function)를 갖는 개미 군집 최적화(Ant Colony Optimization)을 이용한 휴리스틱을 제안하였다. 멀티 비용 함수는 각 개미가 다음 고객 노드로 이동하기 위해 비용을 평가할 때 거리, 요구량, 각도, 시간제약에 대해 서로 다른 가중치를 반영하여 우수한 초기 경로를 구할 수 있도록 한다. 본 연구의 실험결과에서 제안된 휴리스틱이 Solomon I1 휴리스틱과 기회시간이 반영된 하이브리드 휴리스틱보다 효율적으로 최근사 해를 얻을 수 있음을 보였다.

• ETRI Journal
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• v.45 no.3
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• pp.433-447
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• 2023

Critical issues such as connection congestion, long transmission delay, and packet loss become even worse during epidemic, disaster, and so on. In this study, a link load balancing method is proposed to address these issues on the data plane, a plane of the software-defined network (SDN) architecture. These problems are NP-complete, so a meta-heuristic approach, discrete particle swarm optimization, is used with a novel hybrid cost function. The superiority of the proposed method over existing methods in the literature is that it provides link and switch load balancing simultaneously. The goal is to choose a path that minimizes the connection load between the source and destination in multipath SDNs. Furthermore, the proposed work is dynamic, so selected paths are regularly updated. Simulation results prove that with the proposed method, streams reach the target with minimum time, no loss, low power consumption, and low memory usage.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1483-1495
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• 2006

The navigation mesh represents a terrain as a set of triangles on which characters may move around. The navigation mesh cab be generated automatically, and it is more flexible in representing 3D surface. The number of triangles to represent a terrain may vary according to the structure of the terrain. As characters are moving around on a navigation mesh, the path planning can be performed more easily by projecting the 3D surfaces into 2D space. However, when the terrain is represented with an elaborated mesh of large number of triangles to achieve more realistic movements, the path finding can be very inefficient because there are too many states(triangles) to be searched. In this paper, we propose an efficient method of path finding in 3D games where the terrain is represented by navigation meshes. Our method uses the visibility tests. When the graph-based search is applied to elaborated polygonal meshes for detailed terrain representation, the path finding can be very inefficient because there are too many states(polygons) to be searched. In our method, we reduce the search space by using visibility tests so that the search can be fast even on the detailed terrain with large number of polygons. First we find the visible vertices of the obstacles, and define the heuristic function as the distance to the goal through those vertices. By doing that, the number of states that the graph-based search visits can be substantially reduced compared to the plane search with straight-line distance heuristic.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.35-47
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• 2005

This paper is to review a literature concerning Bus Transit Route Network Design(BTRNDP), to describe a future study direction for a systematic application for the BTRNDP. Since a bus transit uses a fixed route, schedule, stop, therefore an approach methodology is different from that of auto network design problem. An approach methodology for BTRNDP is classified by 8 categories: manual & guideline, market analysis, system analytic model. heuristic model. hybrid model. experienced-based model. simulation-based model. mathematical optimization model. In most previous BTRNDP, objective function is to minimize user and operator costs, and constraints on the total operator cost, fleet size and service frequency are common to several previous approach. Transit trip assignment mostly use multi-path trip assignment. Since the search for optimal solution from a large search space of BTRNDP made up by all possible solutions, the mixed combinatorial problem are usually NP-hard. Therefore, previous researches for the BTRNDP use a sequential design process, which is composed of several design steps as follows: the generation of a candidate route set, the route analysis and evaluation process, the selection process of a optimal route set Future study will focus on a development of detailed OD trip table based on bus stop, systematic transit route network evaluation model. updated transit trip assignment technique and advanced solution search algorithm for BTRNDP.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.787-795
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• 2009

This paper presents a histogram equalization based on the logistic function for enhancing the quality of images. The histogram equalization is a simple and effective spatial processing method that it enhances the quality by adjusting the brightness of image. The logistic function that is a nonlinear transformation function is applied to adaptively enhance the brightness of the image according to its intensity level frequency. We propose a flexible and asymmetrical logistic function by only using the intensity level with maximum frequency and the maximum intensity level in an histogram, and the total number of pixels. The proposed function excludes both the computation load of an exponential function and the heuristic setting of an optimal parameter values in the traditional logistic function. The proposed method has been applied for equalizing many images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances and the faster equalizing speed compared with the traditional histogram equalization and the adaptively modified histogram equalization, respectively. And the proposed histogram equalization can be used in various multimedia systems in real-time.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.87-95
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• 1996

A new design scheme for the fuzzy pattern matching classifier (FPMC) is proposed. in conventional design of FPMC, there are no exact information about the membership function of which shape and number critically affect the performance of classifier. So far, a trial and error or heuristic method is used to find membership functions for the input patterns. But each of them have limits in its application to the various types of pattern recognition problem. In this paper, a new method to find the appropriate shape and number of membership functions for the input patterns which minimize classification error is proposed using genetic algorithms(GAs). Genetic algorithms belong to a class of stochastic algorithms based on biological models of evolution. They have been applied to many function optimization problems and shown to find optimal or near optimal solutions. In this paper, GAs are used to find the appropriate shape and number of membership functions based on fitness function which is inversely proportional to classification error. The strings in GAs determine the membership functions and recognition results using these membership functions affect reproduction of next generation in GAs. The proposed design scheme is applied to the several patterns such as tire tread patterns and handwritten alphabetic characters. Experimental results show the usefulness of the proposed scheme.