• Title/Summary/Keyword: search algorithm

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An Application of a Hybrid Genetic Algorithm on Missile Interceptor Allocation Problem (요격미사일 배치문제에 대한 하이브리드 유전알고리듬 적용방법 연구)

  • Han, Hyun-Jin
    • Journal of the military operations research society of Korea
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    • v.35 no.3
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    • pp.47-59
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    • 2009
  • A hybrid Genetic Algorithm is applied to military resource allocation problem. Since military uses many resources in order to maximize its ability, optimization technique has been widely used for analysing resource allocation problem. However, most of the military resource allocation problems are too complicate to solve through the traditional operations research solution tools. Recent innovation in computer technology from the academy makes it possible to apply heuristic approach such as Genetic Algorithm(GA), Simulated Annealing(SA) and Tabu Search(TS) to combinatorial problems which were not addressed by previous operations research tools. In this study, a hybrid Genetic Algorithm which reinforces GA by applying local search algorithm is introduced in order to address military optimization problem. The computational result of hybrid Genetic Algorithm on Missile Interceptor Allocation problem demonstrates its efficiency by comparing its result with that of a simple Genetic Algorithm.

Using Genetic-Fuzzy Methods To Develop User-preference Optimal Route Search Algorithm

  • Choi, Gyoo-Seok;Park, Jong-jin
    • The Journal of Information Technology and Database
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    • v.7 no.1
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    • pp.42-53
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    • 2000
  • The major goal of this research is to develop an optimal route search algorithm for an intelligent route guidance system, one sub-area of ITS. ITS stands for intelligent Transportation System. ITS offers a fundamental solution to various issues concerning transportation and it will eventually help comfortable and swift moves of drivers by receiving and transmitting information on humans, roads and automobiles. Genetic algorithm, and fuzzy logic are utilized in order to implement the proposed algorithm. Using genetic algorithm, the proposed algorithm searches shortest routes in terms of travel time in consideration of stochastic traffic volume, diverse turn constraints, etc. Then using fuzzy logic, it selects driver-preference optimal route among the candidate routes searched by GA, taking into account various driver's preferences such as difficulty degree of driving and surrounding scenery of road, etc. In order to evaluate this algorithm, a virtual road-traffic network DB with various road attributes is simulated, where the suggested algorithm promptly produces the best route for a driver with reference to his or her preferences.

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A Fast Motion Vector Search in Integer Pixel Unit for Variable Blocks Siz (가변 크기 블록에서 정수단위 화소 움직임 벡터의 빠른 검색)

  • 이융기;이영렬
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.5
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    • pp.388-396
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    • 2003
  • In this paper, a fast motion search algorithm that performs motion search for variable blocks in integer pixel unit is proposed. The proposed method is based on the successive elimination algorithm (SEA) using sum norms to find the best estimate of motion vector and obtains the best estimate of the motion vectors of blocks, including 16${\times}$8, 8${\times}$16, and 8${\times}$8, by searching eight pixels around the best motion vector of 16${\times}$16 block obtained from all candidates. And the motion vectors of blocks, including 8${\times}$4, 4${\times}$8, and 4${\times}$4, is obtained by searching eight pixels around the best motion vector of 8${\times}$8 block. The proposed motion search is applied to the H.264 encoder that performs variable blocks motion estimation (ME). In terms of computational complexity, the proposed search algorithm for motion estimation (ME) calculates motion vectors in about 23.8 times speed compared with the spiral full search without early termination and 4.6 times speed compared with the motion estimation method using hierarchical sum of absolute difference (SAD) of 4${\times}$4 blocks, while it shows 0.1dB∼0.4dB peak signal-to-noise ratio (PSNR) drop in comparison to the spiral full search.

A Prediction Search Algorithm by using Temporal and Spatial Motion Information from the Previous Frame (이전 프레임의 시공간 모션 정보에 의한 예측 탐색 알고리즘)

  • Kwak, Sung-Keun;Wee, Young-Cheul;Kimn, Ha-Jine
    • Journal of the Korea Computer Graphics Society
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    • v.9 no.3
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    • pp.23-29
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    • 2003
  • There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of the previous block. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. In this paper, we propose the block-matching motion estimation using an adaptive initial search point by the predicted motion information from the same block of the previous frame. And the first search point of the proposed algorithm is moved an initial point on the location of being possibility and the searching process after moving the first search point is processed according to the fast search pattern. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved UP to the 1.05dB as depend on the image sequences and improved about 0.33~0.37dB on an average. Search times are reduced about 29~97% than the other fast search algorithms. Simulation results also show that the performance of the proposed scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

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Fast Multiuser Detection in CDMA Systems Using Gradient Guided Search (Gradient Guided 탐색을 이용한 고속 CDMA 다중사용자 검출)

  • Choi, Yang-Ho
    • Journal of Industrial Technology
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    • v.24 no.B
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    • pp.143-148
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    • 2004
  • We present a fast algorithm for CDMA (code division multiple access) multiuser detection using the gradient guided search. The fast algorithm calculates the maximum likelihood (ML) metric so efficiently that it needs only O(K) additions in the presence of K users once some initialization is completed. The computational advantages of the fast algorithm over the conventional method are more noticeable as more iterations are required to obtain a suboptimal solution as in the initialization with matched filters.

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A Study of Search Space Clustering Algorithm for Steered Response Power (Steered Response Power를 위한 검색 공간 클러스터링 연구)

  • Chung, Jae-Youn;Yook, Dong-Suk
    • Proceedings of the KSPS conference
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    • 2006.11a
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    • pp.88-91
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    • 2006
  • Steered response power(SRP) based algorithm uses a focused beamformer which steers the array to various locations and searches for a peak in output power to localize sound sources. SRP-PHAT, a phase transformed SRP, shows high accuracy, but requires a large amount of computation time. This paper proposes an algorithm that clusters search spaces in advance to reduce computation time of SRP based algorithms.

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Maximum Likelihood Estimation for the Laplacian Autoregressive Time Series Model

  • Son, Young-Sook;Cho, Sin-Sup
    • Journal of the Korean Statistical Society
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    • v.25 no.3
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    • pp.359-368
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    • 1996
  • The maximum likelihood estimation is discussed for the NLAR model with Laplacian marginals. Since the explicit form of the estimates cannot be obtained due to the complicated nature of the likelihood function we utilize the automatic computer optimization subroutine using a direct search complex algorithm. The conditional least square estimates are used as initial estimates in maximum likelihood procedures. The results of a simulation study for the maximum likelihood estimates of the NLAR(1) and the NLAR(2) models are presented.

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Optimized Binary-Search-on- Range Architecture for IP Address Lookup (IP 주소 검색을 위한 최적화된 영역분할 이진검색 구조)

  • Park, Kyong-Hye;Lim, Hye-Sook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.12B
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    • pp.1103-1111
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    • 2008
  • Internet routers forward an incoming packet to an output port toward its final destination through IP address lookup. Since each incoming packet should be forwarded in wire-speed, it is essential to provide the high-speed search performance. In this paper, IP address lookup algorithms using binary search are studied. Most of the binary search algorithms do not provide a balanced search, and hence the required number of memory access is excessive so that the search performance is poor. On the other hand, binary-search-on-range algorithm provides high-speed search performance, but it requires a large amount of memory. This paper shows an optimized binary-search-on-range structure which reduces the memory requirement by deleting unnecessary entries and an entry field. By this optimization, it is shown that the binary-search-on-range can be performed in a routing table with a similar or lesser number of entries than the number of prefixes. Using real backbone routing data, the optimized structure is compared with the original binary-search-on-range algorithm in terms of search performance. The performance comparison with various binary search algorithms is also provided.

A Tabu Search Algorithm for Controller Placement Problem in Software Defined Networks (소프트웨어 정의 네트워크에서 제어기 배치 문제를 위한 타부 서치 알고리즘)

  • Jang, Kil-woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.3
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    • pp.491-498
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    • 2016
  • The software defined networks implement a software network control plane, which is physically separated from the data plane. For wide area software defined network deployments, multiple controllers are required, and the placement of these controllers influences importantly the performance of the software defined networks. This paper proposes a Tabu search algorithm, which is one of the meta heuristic algorithms, for an efficient controller placement in software defined networks. In order to efficiently obtain better results, we propose new neighborhood generating operations, which are called the neighbor position move and the neighbor number move, of the Tabu search algorithm. We evaluate the performances of the proposed algorithm through some experiments in terms of the minimum latency and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms the existing genetic algorithm and random method under various conditions.

A Multiple Vehicle Object Detection Algorithm Using Feature Point Matching (특징점 매칭을 이용한 다중 차량 객체 검출 알고리즘)

  • Lee, Kyung-Min;Lin, Chi-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.1
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    • pp.123-128
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    • 2018
  • In this paper, we propose a multi-vehicle object detection algorithm using feature point matching that tracks efficient vehicle objects. The proposed algorithm extracts the feature points of the vehicle using the FAST algorithm for efficient vehicle object tracking. And True if the feature points are included in the image segmented into the 5X5 region. If the feature point is not included, it is processed as False and the corresponding area is blacked to remove unnecessary object information excluding the vehicle object. Then, the post processed area is set as the maximum search window size of the vehicle. And A minimum search window using the outermost feature points of the vehicle is set. By using the set search window, we compensate the disadvantages of the search window size of mean-shift algorithm and track vehicle object. In order to evaluate the performance of the proposed method, SIFT and SURF algorithms are compared and tested. The result is about four times faster than the SIFT algorithm. And it has the advantage of detecting more efficiently than the process of SUFR algorithm.