• Korean Management Science Review
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• v.26 no.1
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• pp.65-76
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• 2009

The undirected Steiner tree problem in graphs is known to be NP-hard. The objective of this problem is to find a shortest tree containing a subset of nodes, called terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step. graph reduction rules eliminate useless nodes and edges which do not contribute to make an optimal solution. In the second step, a max-min ant colony optimization combined with Prim's algorithm is developed to solve the reduced problem. The proposed algorithm is tested in the sets of standard test problems. The results show that the algorithm efficiently presents very correct solutions to the benchmark problems.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.311-312
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• 2007

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the Maklink graph method. At first, we produce the path of a mobile robot a the static environment. And then we find midpoints of each path using the Maklink graph. Finally the ant colony optimization algorithm is adopted to get a shortest path. In this paper, we prove the performance of the proposed algorithm is better than that of the Dijkstra algorithm through simulation.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.175-182
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• 2011

고객의 요구에 대한 빠른 대응과 유연하고 효율적으로 새로운 제품을 적기에 개발하기 위해서는 제품 플랫폼에 기초한 대량 맞춤이 절실히 요구된다. 이러한 목적을 달성하기 위하여 기업들은 상대적으로 생산비용을 낮게 유지하면서 대량생산의 이점을 유지하고 동시에 고객의 요구사항을 만족시키기 위해, product family를 도입하고 가능하면 작은 변화를 통하여 제품의 다양성을 유지하고자 한다. Product family를 설계할 때 중요한 이슈 중에 하나는 제품의 공통성과 차별성간의 절충점을 찾아내는 것인데, 본 연구에서는 설계자들이 product family 재설계를 용이하게 하기 위한 방법론을 제안한다. 이를 위하여 본 연구에서는 ant colony 알고리즘과 product family의 공통성 평가지수를 이용하여 product family 재설계 방법론을 개발한다. 제안한 방법론은 복잡하고 반복적인 많은 계산과정을 가지고 있는 다른 방법과 달리 메타 휴리스틱 알고리즘을 적용하여 인간의 간섭을 줄이고, 실험결과의 정확도, 반복성 및 강건성을 향상시킨다. 본 연구에서는 컴퓨터 마우스 제품군을 대상으로 제안한 방법의 타당성을 검증하였고, 추가적으로 product family 레벨과 부품 레벨의 product family 재설계 추천방안도 제시하였다.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1208-1222
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• 2024

Music resources are characterized by quantization, diversification and complication. With the rapid increase of the demand for music resources, the storage of music resources is very large. In order to improve the retrieval effect of music resources, a massive music resources retrieval method based on ant colony algorithm is proposed to effectively use music resources. This paper constructs autocorrelation function to extract pitch feature of music resource, classifies the music resource information by calculating feature similarity. Using ant colony algorithm to correlate the feature of music resource, gain the result of correlative, locate the result of detection and get the result of multi-module. Simulation results show that the proposed method has high precision and recall, short retrieval time and can effectively retrieve massive music resources.

• Journal of Korea Game Society
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• v.16 no.5
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• pp.7-22
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• 2016

The risk is subjectively perceived by the subject to judge. In the case of the game, game organizations and watchdog groups also recognized differently occurrence probability and intensity of risk to form a physical relationships of the game with each. Thus, we look only at the risk of their own subjective opinion, the fundamental solution is not possible. In this paper, we conducted a study on the form, occurrence point, and generating processes of risk by analyzing the physical components that make up the network of the game based on ATN in order to confirm definitely the substance and the presence of the game risk. In view of ANT, the game and humans constitute a network through their ability to act as each actor. If the gamer does not clearly recognize the nature of the ability to act of the game, the reverse control and the excess flow occur through remediation properties of the game. Therefore, it requires a more in-depth study in the future with respect to complex structure and relationships of the game-gamer network.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.751-756
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• 2003

Ant Colony Optimization (ACO) is new meta heuristics method to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was firstly proposed for tackling the well known Traveling Salesman Problem (TSP) . In this paper, we introduce Multi Colony Ant Model that achieve positive interaction and negative interaction through Intensification and Diversification to improve original ACS performance. This algorithm is a method to solve problem through interaction between ACS groups that consist of some agent colonies to solve TSP problem. In this paper, we apply this proposed method to TSP problem and evaluates previous method and comparison for the performance and we wish to certify that qualitative level of problem solution is excellent.

• Korean journal of applied entomology
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• v.47 no.1
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• pp.107-110
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• 2008

Tropical fire ant, Solenopsis geminata (Fabricius) is distributed over the tropical and temperate areas. It is a polyphagous pest attacking to various plant and causes the pain to the people doing outdoor work. So it is known for a hygienic pest to human being, especially the people doing outdoor activities. It can cause severe pain to human, even with just a bite. Of particular concern is the possibility of its settlement in this country, if it invade to the farmlands and/or forests of Jeju Island and southern part in Korea. It is listed as a regulated pest in Plant Quarantine Act of Korea. This ant is usually imported through a ship and early settled in the port area where it is already distributed. Recently its distribution is rapidly spreading into Southeast Asia and southern part of China. In Korea, it was detected the one time in 1990s, but was detected the ten times from 2000 to 2006 by an imported plant quarantine process. Therefore, we would like to provide some information on the species, including morphology, distribution, host plant, damaged symptom and its general bionomics, which will be useful data for plant quarantine process and control.

• The KIPS Transactions:PartB
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• v.16B no.3
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• pp.195-202
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• 2009

In this paper, we propose the regions segmentation method of the white matter and the gray matter for brain MR image by using the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. This algorithm finds the expected pixel for image as the real ant finds the food from nest to food source. Then ants deposit pheromone on the pixels, and the pheromone will affect the motion of next ants. At each iteration step, ants will change their positions in the image according to the transition rule. Finally, we can obtain the segmentation results through analyzing the pheromone distribution in the image. We compared the proposed method with other threshold methods, viz. the Otsu' method, the genetic algorithm, the fuzzy method, and the original ant colony optimization algorithm. From comparison results, the proposed method is more exact than other threshold methods for the segmentation of specific region structures in MR brain image.

• Korean journal of applied entomology
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• v.54 no.4
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• pp.327-333
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• 2015

In order to identify the post-fire changes of ant assemblages after a forest fire, ants were surveyed at three survey sites (artificial reforestation site, natural reforestation site, and unburned forest site) in a burned forest area for eight years from 2005 using pitfall traps. 24 species were collected, and Nylanderia flavipes was the most abundant. Ant species preferring forest habitats (e.g. Aphaenogaster japonica. Lasius spathepus, and Plagiolepis flavescens) more occurred at the unburned forest site and the natural reforestation site, whereas ant species preferring open habitat (e.g., Formica japonica, Camponotus japonicus, and Tetramorium caespitum) more occurred at the artificial reforestation site. Ordination analysis indicated that ant communities of the artificial reforestation site were more changed compared with those of the natural reforestation site after the fire. The communities of the natural reforestation site were restored to the pre-fire state in five to six years after fire, whereas those of the artificial forest site seemed to take about 25 years to restore.