• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2132-2134
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• 2001

We propose an Tabu search changing neighborhood solution's range to be searched each iteration according to an objective function. It is applied for designing the scaling factors of Fuzzy Logic Controller (FLC) using the proposed Tabu search. We apply it to the speed control of AC Servomotor to evaluate the usefulness of the proposed method. As a result of the computer simulation, the FLC shows the better performance than PI controller in terms of overshoot and settling time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.251-257
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• 2018

We will be establish the new k stores of identical product firm $F_B$ to gain competitive advantage over rival firm $F_A$ that has already monopolize a market with k stores. In this situation, how we can decide the location of k stores? For this problem, Serra and Revelle proposes k-Median and MAXCAP integer programming using LP+BB to decide the k stores of firm $F_B$. Then they exchange the k stores to another location that cover more customers. This paper suggests non-neighborhood search method that finds the ${\upsilon}{\not\in}N_G(u)$nodes for u of firm $F_A$ without most outer loop nodes using just MS-Excel. As a result of experiment, the proposed algorithm can be get the optimal solution easier and faster than integer programming.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.213-220
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• 2018

This paper deals with survival facility location problem(SFLP) that the store with less of demand threshold level is closed result from another new establishment of store in the same kind of comparative firms have a monopoly market. We will be faced with a difficult problem when a new establishment stores in market saturation that the closed stores more than opening stores. Serra et al. proposes recursive heuristic concentration algorithm, and Han et al. suggests maximum insurance of customer location. But the drawback of these algorithms is a recursively computation for many locations. This paper get the solution from only neighborhood search of comparative firm's stores that can be maximum customers and closed comparative firm's store, and the location with minimum customer exchange to the location that can be closed the comparative firm's store with maximum customer. The advantage of this algorithm is to get the solution using a MS-Excel.

• ETRI Journal
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• v.28 no.6
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• pp.721-731
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• 2006

A fast intra skip detection algorithm based on the ratedistortion (RD) cost for an inter frame (P-slices) is proposed for H.264/AVC video encoding. In the H.264/AVC coding standard, a robust rate-distortion optimization technique is used to select the best coding mode and reference frame for each macroblock (MB). There are three types of intra predictions according to profiles. These are $16{\times}16$ and $4{\times}4$ intra predictions for luminance and an $8{\times}8$ intra prediction for chroma. For the high profile, an $8{\times}8$ intra prediction has been added for luminance. The $4{\times}4$ prediction mode has 9 prediction directions with 4 directions for $16{\times}16$ and $8{\times}8$ luma, and $8{\times}8$ chrominance. In addition to the inter mode search procedure, an intra mode search causes a significant increase in the complexity and computational load for an inter frame. To reduce the computational load of the intra mode search at the inter frame, the RD costs of the neighborhood MBs for the current MB are used and we propose an adaptive thresholding scheme for the intra skip extraction. We verified the performance of the proposed scheme through comparative analysis of experimental results using joint model reference software. The overall encoding time was reduced up to 32% for the IPPP sequence type and 35% for the IBBPBBP sequence type.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.236-244
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• 2012

The minimum energy broadcast problem is for all deployed nodes to minimize a total transmission energy for performing a broadcast operation in wireless networks. In this paper, we propose a Tabu search algorithm to solve efficiently the minimum energy broadcast problem on the basis of meta-heuristic approach in wireless sensor networks. In order to make a search more efficient, we propose a novel neighborhood generating method and a repair function of the proposed algorithm. We compare the performance of the proposed algorithm with other existing algorithms through some experiments in terms of the total transmission energy of nodes and algorithm computation time. Experimental results show that the proposed algorithm is efficient for the minimum energy broadcast problem in wireless sensor networks.

• Convergence Security Journal
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• v.19 no.2
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• pp.73-81
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• 2019

In this paper, we propose a user-dependent mid-point navigation system using a time weighted mid-point navigation algorithm and a user preference based mid-point neighborhood recommendation system. The proposed system consists of a mid-point navigation module for calculating an mid-point by applying a time weight of each user based on a departure point between users, and a search module for providing a search for a route to the calculated mid-point. In addition, based on the mid-point search result, it is possible to increase the utilization rate of users by including a place recommending function based on user's preference. Experimental results show that the proposed system can increase the efficiency of using by the user-dependent mid-point navigation and place recommendation function.

• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.689-712
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• 2019

Time-series models like AR-ARX and ARMAX, provide a robust way to capture the dynamic properties of structures, and their residuals can be effectively used as features for damage detection. Even though several research papers discuss the implementation of AR-ARX and ARMAX models for damage diagnosis, they are basically been exploited so far for detecting the time instant of damage and also the spatial location of the damage. However, the inverse problem associated with damage quantification i.e. extent of damage using time series models is not been reported in the literature. In this paper, an approach to detect the extent of damage by combining the ARMAX model by formulating the inverse problem as a multi-constrained optimization problem and solving using a newly developed hybrid adaptive differential search with dynamic interaction is presented. The proposed variant of the differential search technique employs small multiple populations which perform the search independently and exchange the information with the dynamic neighborhood. The adaptive features and local search ability features are built into the algorithm in order to improve the convergence characteristics and also the overall performance of the technique. The multi-constrained optimization formulations of the inverse problem, associated with damage quantification using time series models, attempted here for the first time, can considerably improve the robustness of the search process. Numerical simulation studies have been carried out by considering three numerical examples to demonstrate the effectiveness of the proposed technique in robustly identifying the extent of the damage. Issues related to modeling errors and also measurement noise are also addressed in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.929-935
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• 2017

All sensor nodes generally determine their positions using anchor nodes that are located in underwater sensor networks. This paper proposes a Tabu search algorithm to determine the minimum number of anchor nodes for the location of all sensor nodes in underwater sensor networks. As the number of the sensor nodes increases in the network, the amount of calculation that determines the number of anchor nodes would be too much increased. In this paper, we propose a Tabu search algorithm that determines the minimum number of anchor nodes within a reasonable computation time in a high dense network, and propose an efficient neighborhood generating operation of the Tabu search algorithm for efficient search. The proposed algorithm evaluates those performances through some experiments in terms of the minimum number of anchor nodes and execution time. The proposed algorithm shows 5-10% better performance than the conventional algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.83-90
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• 2015

This paper proposes a Tabu search algorithm to maximize the connectivity between the router nodes and the client nodes in wireless mesh networks. As the number of the router nodes and the client nodes in the networks increases, the amount of calculation for finding the solution would be too much increased. To obtain the optimal solution within a reasonable computation time for a high-density network, we propose a Tabu search algorithm to obtain the optimal solution for maximizing the connectivity. In order to make a search more efficient, we propose some efficient neighborhood generating operations of the Tabu search algorithm. We evaluate those performances through some experiments in terms of the maximum number of the connectivity and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.3
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• pp.25-43
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• 2010

We consider a multi-objective balancing and sequencing problem in mixed model assembly lines, which is important for an efficient use of the assembly lines. In this paper, we present a neighborhood symbiotic evolutionary algorithm to simultaneously solve the two problems of balancing and model sequencing under multiple objectives. We aim to find a set of well-distributed solutions close to the true Pareto optimal solutions for decision makers. The proposed algorithm has a two-leveled structure. At Level 1, two populations are operated : One consists of individuals each of which represents a partial solution to the balancing problem and the other consists of individuals for the sequencing problem. Level 2, which is an upper level, works one population whose individuals represent the combined entire solutions to the two problems. The process of Level 1 imitates a neighborhood symbiotic evolution and that of Level 2 simulates an endosymbiotic evolution together with an elitist strategy to promote the capability of solution search. The performance of the proposed algorithm is compared with those of the existing algorithms in convergence, diversity and computation time of nondominated solutions. The experimental results show that the proposed algorithm is superior to the compared algorithms in all the three performance measures.