• Journal of Digital Contents Society
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• v.15 no.5
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• pp.651-661
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• 2014

The complexity to search a specific content over TV platform is drastically increasing. Based on previous studies from computer data management system, we propose a new method that helps users to search and select content effectively. In general, contents over computers are represented by spatial metaphor, which replicates our physical environment and value systems about space. We suggest 3D lattice structure to construct information space for TV platform. Users can infer relevance between contents via special clue in information space, so as to select content more easily. Also, they can search contents through its temporal property that also represented in space. We make full use of our natural capability that can reduce additional overload to learning new interface. The results of this study can be significant and heuristic contributions, as they can be applied to diverse service areas utilizing video contents.

• Journal of the Korean Society of Hazard Mitigation
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• v.6 no.2 s.21
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• pp.51-60
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• 2006

The objective of this research is to develop a least cost system design method for branched storm sewer systems while satisfying all the design constraints using heuristic techniques such as genetic algorithm and harmony search. Two sewer system models have been developed in this study. The SEWERGA and SEWERHS both determine the optimal discrete pipe installation depths as decision variables. Two models also determine the optimal diameter of sewer pipes using the discrete installation depths of the pipes while satisfying the discharge and velocity requirement constraints at each pipe. Two models are applied to the example that was originally solved by Mays and Yen (1975) using their dynamic programming(DP). The optimal costs obtained from SEWERGA and SEWERHS are about 4% lower than that of the DP approach.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1193-1201
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• 2020

Cell planning, which determines the cell structure for location management of mobile terminals in mobile communications, has been dealt with as an important research task to determine network performance. Among the factors influencing the cell structure planning in mobile communication, the signal cost for location management plays the most important role. In this paper, we propose an optimization algorithm that minimizes the location management cost of all the cells used to plan the cell structure in the network with reporting cell structure in mobile communication. The proposed algorithm uses a Tabu search algorithm, which is a meta-heuristic algorithm, and the proposed algorithm proposes a new neighborhood generation method to obtain a result close to the optimal solution. In order to evaluate the performance of the proposed algorithm, the simulation was performed in terms of location management cost and algorithm execution time. The evaluation results show that the proposed algorithm outperforms the existing genetic algorithm and simulated annealing.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.540-548
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• 2012

The Weapon Target Allocation(WTA) problem is the NP-Complete problem. The WTA problem is that the threatful air targets are assigned by weapon of allies for killing the targets. A good solution of NP-complete problem is heuristic algorithms. Genetic algorithms are commonly used heuristic for global optimization, and it is good solution on the diverse problem domain. But there has been very little research done on the generation of their initial population. The initialization of population is one of the GA step, and it decide to initial value of individuals. In this paper, we propose to the population initialization method to improve a Genetic Algorithm. When it initializes population, the proposed algorithm reflects the characteristics of the WTA problem domain, and inherits the dominant gene. In addition, the search space widely spread in the problem space to find efficiently the good quality solution. In this paper, the proposed algorithm to verify performance examine that an analysis of various properties and the experimental results by analyzing the performance compare to other algorithms. The proposed algorithm compared to the other initialization methods and a general genetic algorithm. As a result, the proposed algorithm showed better performance in WTA problem than the other algorithms. In particular, the proposed algorithm is a good way to apply to the variety of situation WTA problem domain, because the proposed algorithm can be applied flexibly to WTA problem by the adjustment of RMI.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.80-90
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• 2002

Clustering is a useful technique for grouping data points such that points within a single group/cluster have similar characteristics. Many clustering algorithms have been developed and used in engineering applications including pattern recognition and image processing etc. Recently, it has drawn increasing attention as one of important techniques in data mining. However, clustering algorithms such as K-means and Fuzzy C-means suffer from difficulties. Those are the needs to determine the number of clusters apriori and the clustering results depending on the initial set of clusters which fails to gain desirable results. In this paper, we propose a new clustering algorithm, which solves mentioned problems. In our method we use evolutionary algorithm to solve the local optima problem that clustering converges to an undesirable state starting with an inappropriate set of clusters. We also adopt a new measure that represents how well data are clustered. The measure is determined in terms of both intra-cluster dispersion and inter-cluster separability. Using the measure, in our method the number of clusters is automatically determined as the result of optimization process. And also, we combine heuristic that is problem-specific knowledge with a evolutionary algorithm to speed evolutionary algorithm search. We have experimented our algorithm with several sets of multi-dimensional data and it has been shown that one algorithm outperforms the existing algorithms.

• Journal of KIISE:Information Networking
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• v.35 no.5
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• pp.367-373
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• 2008

Recently, the NAT middlebox widely deployed in the home network environment prohibits DM operations from reaching user devices behind NAT. In this article, we focus on NAT issues to manage home network devices. Particularly, we discuss standardization efforts, and present our proposal to deploy DM services for VoIP and IPTV devices under NAT. By slightly changing behaviors of Simple Network Management Protocol (SNMP) Manager and Agent, and defining additional Management Objects (MOs) to gather NAT binding information, we could solve the NAT traversal problem under symmetric NAT. Moreover, we propose an enhanced method to search the UDP hole binding time of the NAT box. We applied our method to randomly selected 22 VoIP devices out of 194 NATed hosts in the real broadband network and have achieved 99% of the success ratio for exchanging SNMP request messages and 26% of enhancement for searching the UDP hole binding time.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.1-9
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• 2005

In this paper, we suggest multi colony interaction ant reinforcement learning model. This method is a hybrid of multi colony interaction by elite strategy and reinforcement teaming applying Temporal Difference(TD) learning to Ant-Q loaming. Proposed model is consisted of some independent AS colonies, and interaction achieves search according to elite strategy(Intensification, Diversification strategy) between the colonies. Intensification strategy enables to select of good path to use heuristic information of other agent colony. This makes to select the high frequency of the visit of a edge by agents through positive interaction of between the colonies. Diversification strategy makes to escape selection of the high frequency of the visit of a edge by agents achieve negative interaction by search information of other agent colony. Through this strategies, we could know that proposed reinforcement loaming method converges faster to optimal solution than original ACS and Ant-Q.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.930-939
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• 2021

In recent years, the use of broadband bandwidth and redundant links for stable transmission in networks has resulted in excessive energy consumption and reduced transmission efficiency. In this paper, we propose an optimization algorithm that reduces the number of transmission links and minimizes transmission energy by removing redundant traffic in networks where traffic redundancy is allowed. The optimization algorithm proposed in this paper uses the meta-heuristic method using Tabu search algorithm. The proposed optimization algorithm minimizes transmission energy by designing a neighborhood generation method that efficiently routes overlapping traffic. The performance evaluation of the proposed optimization algorithm was performed in terms of the number of links used to transmit all traffic generated in the network and the transmission energy consumed. From the performance evaluation results, it was confirmed that the proposed algorithm is superior to other algorithms previously proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.572-580
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• 2021

In order to reduce transmission delay and increase reliability in networks, mainly high-performance and high-power network equipment is used to guarantee network quality. In this paper, we propose an optimization algorithm to minimize the energy consumed when transmitting traffic in networks with a bundle link composed of multiple physical cables. The proposed optimization algorithm is a meta-heuristic method, which uses tabu search algorithm. In addition, it is designed to minimize transmission energy by minimizing the cables on the paths of the source and destination nodes for each traffic. In the proposed optimization algorithm, performance evaluation was performed in terms of the number of cables used in the transmission and the link utilization for all traffic on networks, and the performance evaluation result confirmed the superior performance than the previously proposed method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.361-366
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• 2006

It is widely known that the dynamic optimal path algorithm, adopting real-time path finding, can be supporting an optimal route with which users are satisfied economically and accurately. However, this system has to search optimal routes frequently for updating them. The proposed concept of optimizing search area lets it reach heuristic optimal path rapidly and efficiently. Since optimal path should be increased in proportion to an distance between origin and destination, tremendous calculating time and highly efficient computers are required for searching long distance journey. In this paper, as a result of which the concepts of partial solution and representative path are suggested. It was possible to find an optimal route by decreasing a half area in comparison with the previous method. Furthermore, as the size of the searching area is uniform, comparatively low efficient computer is required for long distance trip.