• Title/Summary/Keyword: iterative search

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An Iterative Local Search Algorithm for Rural Postman Problems (Rural Postman Problem 해법을 위한 Iterative Local Search 알고리즘)

  • 강명주
    • Journal of the Korea Society of Computer and Information
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    • v.7 no.1
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    • pp.48-53
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    • 2002
  • This paper Proposes an iterative Local Search (ILS) algorithm for Rural Postman Problems (RPPs). LS searches neighbors from an initial solution in solution space and obtains a nearoptimal solution which can be a local-minima. As an extension of LS, the ILS algorithm is a method that uses various initial solutions for LS. Hence. ILS can overcome the defect of LS. This paper proposes LS and ILS methods for 18 RPPs and analyzes the results of LS and ILS. In the simulation results, the ILS method obtained the better results than the LS method.

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Iterative Cyclic Model of Generation MZ's Consumer Purchase Decision Journey for a Fashion Product (MZ세대 소비자의 패션상품 구매의사결정여정의 반복순환모델)

  • Lee, Jung-Woo;Kim, Mi Young
    • Journal of the Korean Society of Clothing and Textiles
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    • v.46 no.4
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    • pp.638-656
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    • 2022
  • This study aimed to identify characteristics of Generation MZ's consumer purchase decision journey to develop the new fashion CDJ model. The initial stage was affected by habit, online community, social media, aesthetics, circumstantial need, and proxy. In the search and consideration stage, mobile channels were used actively. In the active search and evaluation stage, online media, experiential data, and personal information were employed. In the purchase stage, zoomers took plenty of time in search and evaluation before spending, contrary to millennials who made their purchases more quickly. In the post-purchase experience stage, zoomers actively displayed follow-up behaviors depending on their satisfaction, such as retaining or deleting the app. While, millennials did not turn away from the store or brand, but followed up on their purchases even when they had an unsatisfactory experience. Based on the characteristics of CDJ, iterative cycle CDJ models were developed. Zoomers CDJ model was presented as a search loop that consists of the search and evaluation process, in which information accumulates, and a purchase loop in which the actual purchase occurs. The iterative cycle CDJ model was presented connected to the loyalty loop as the main section, which is accelerated in millennials' CDJ model.

Clipping Value Estimate for Iterative Tree Search Detection

  • Zheng, Jianping;Bai, Baoming;Li, Ying
    • Journal of Communications and Networks
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    • v.12 no.5
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    • pp.475-479
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    • 2010
  • The clipping value, defined as the log-likelihood ratio (LLR) in the case wherein all the list of candidates have the same binary value, is investigated, and an effective method to estimate it is presented for iterative tree search detection. The basic principle behind the method is that the clipping value of a channel bit is equal to the LLR of the maximum probability of correct decision of the bit to the corresponding probability of erroneous decision. In conjunction with multilevel bit mappings, the clipping value can be calculated with the parameters of the number of transmit antennas, $N_t$; number of bits per constellation point, $M_c$; and variance of the channel noise, $\sigma^2$, per real dimension in the Rayleigh fading channel. Analyses and simulations show that the bit error performance of the proposed method is better than that of the conventional fixed-value method.

Combined Traffic Signal Control and Traffic Assignment : Algorithms, Implementation and Numerical Results

  • Lee, Chung-Won
    • Proceedings of the KOR-KST Conference
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    • 2000.02a
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    • pp.89-115
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    • 2000
  • Traffic signal setting policies and traffic assignment procedures are mutually dependent. The combined signal control and traffic assignment problem deals with this interaction. With the total travel time minimization objective, gradient based local search methods are implemented. Deterministic user equilibrium is the selected user route choice rule, Webster's delay curve is the link performance function, and green time per cycle ratios are decision variables. Three implemented solution codes resulting in six variations include intersections operating under multiphase operation with overlapping traffic movements. For reference, the iterative approach is also coded and all codes are tested in four example networks at five demand levels. The results show the numerical gradient estimation procedure performs best although the simplified local searches show reducing the large network computational burden. Demand level as well as network size affects the relative performance of the local and iterative approaches. As demand level becomes higher, (1) in the small network, the local search tends to outperform the iterative search and (2) in the large network, vice versa.

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Iterative Generalized Hough Transform using Multiresolution Search (다중해상도 탐색을 이용한 반복 일반화 허프 변환)

  • ;W. Nick Street
    • Journal of KIISE:Software and Applications
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    • v.30 no.10
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    • pp.973-982
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    • 2003
  • This paper presents an efficient method for automatically detecting objects in a given image. The GHT is a robust template matching algorithm for automatic object detection in order to find objects of various shapes. Many different templates are applied by the GHT in order to find objects of various shapes and size. Every boundary detected by the GHT scan be used as an initial outline for more precise contour-finding techniques. The main weakness of the GHT is the excessive time and memory requirements. In order to overcome this drawback, the proposed algorithm uses a multiresolution search by scaling down the original image to half-sized and quarter-sized images. Using the information from the first iterative GHT on a quarter-sized image, the range of nuclear sizes is determined to limit the parameter space of the half-sized image. After the second iterative GHT on the half-sized image, nuclei are detected by the fine search and segmented with edge information which helps determine the exact boundary. The experimental results show that this method gives reduction in computation time and memory usage without loss of accuracy.

Fast Warping Prediction using Bit-Pattern for Motion Estimation (비트패턴을 이용한 고속 워핑 예측)

  • 강봉구;안재형
    • Journal of Korea Multimedia Society
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    • v.4 no.5
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    • pp.390-395
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    • 2001
  • In this paper, we propose a fast warping prediction using bit-pattern for motion estimation. Because of the spatial dependency between motion vectors of neighboring node points carrying motion information, the optimization of motion search requires an iterative search. The computational load stemming from the iterative search is one of the major obstacles for practical usage of warping prediction. The motion estimation in the proposed algorithm measures whether the motion content of the area is or not, using bit-pattern. Warping prediction using the motion content of the area make the procedure of motion estimation efficient by eliminating an unnecessary searching. Experimental results show that the proposed algorithm can reduce more 75% iterative search while maintaining performances as close as the conventional warping prediction.

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An Iterative Insertion Algorithm and a Hybrid Meta Heuristic for the Traveling Salesman Problem with Time Windows (시간제약이 있는 외판원 문제를 위한 메타휴리스틱 기법)

  • Kim, Byung-In
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.1
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    • pp.86-98
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    • 2007
  • This paper presents a heuristic algorithm for the traveling salesman problem with time windows (TSPTW). Aniterative insertion algorithm as a constructive search heuristic and a hybrid meta heuristic combining simulatedannealing and tabu search with the randomized selection of 2-interchange and a simple move operator as animproving search heuristic are proposed, Computational tests performed on 400 benchmark problem instancesshow that the proposed algorithm generates optimal or near-optimal solutions in most cases. New best knownheuristic values for many benchmark problem sets were obtained using the proposed approach.

ON STRONG CONVERGENCE THEOREMS FOR A VISCOSITY-TYPE TSENG'S EXTRAGRADIENT METHODS SOLVING QUASIMONOTONE VARIATIONAL INEQUALITIES

  • Wairojjana, Nopparat;Pholasa, Nattawut;Pakkaranang, Nuttapol
    • Nonlinear Functional Analysis and Applications
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    • v.27 no.2
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    • pp.381-403
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    • 2022
  • The main goal of this research is to solve variational inequalities involving quasimonotone operators in infinite-dimensional real Hilbert spaces numerically. The main advantage of these iterative schemes is the ease with which step size rules can be designed based on an operator explanation rather than the Lipschitz constant or another line search method. The proposed iterative schemes use a monotone and non-monotone step size strategy based on mapping (operator) knowledge as a replacement for the Lipschitz constant or another line search method. The strong convergences have been demonstrated to correspond well to the proposed methods and to settle certain control specification conditions. Finally, we propose some numerical experiments to assess the effectiveness and influence of iterative methods.

Fast Millimeter-Wave Beam Training with Receive Beamforming

  • Kim, Joongheon;Molisch, Andreas F.
    • Journal of Communications and Networks
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    • v.16 no.5
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    • pp.512-522
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    • 2014
  • This paper proposes fast millimeter-wave (mm-wave) beam training protocols with receive beamforming. Both IEEE standards and the academic literature have generally considered beam training protocols involving exhaustive search over all possible beam directions for both the beamforming initiator and responder. However, this operation requires a long time (and thus overhead) when the beamwidth is quite narrow such as for mm-wave beams ($1^{\circ}$ in the worst case). To alleviate this problem, we propose two types of adaptive beam training protocols for fixed and adaptive modulation, respectively, which take into account the unique propagation characteristics of millimeter waves. For fixed modulation, the proposed protocol allows for interactive beam training, stopping the search when a local maximum of the power angular spectrum is found that is sufficient to support the chosen modulation/coding scheme. We furthermore suggest approaches to prioritize certain directions determined from the propagation geometry, long-term statistics, etc. For adaptive modulation, the proposed protocol uses iterative multi-level beam training concepts for fast link configuration that provide an exhaustive search with significantly lower complexity. Our simulation results verify that the proposed protocol performs better than traditional exhaustive search in terms of the link configuration speed for mobile wireless service applications.

Low Complexity Iterative Detection and Decoding using an Adaptive Early Termination Scheme in MIMO system (다중 안테나 시스템에서 적응적 조기 종료를 이용한 낮은 복잡도 반복 검출 및 복호기)

  • Joung, Hyun-Sung;Choi, Kyung-Jun;Kim, Kyung-Jun;Kim, Kwang-Soon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.8C
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    • pp.522-528
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    • 2011
  • The iterative detection and decoding (IDD) has been shown to dramatically improve the bit error rate (BER) performance of the multiple-input multiple-output (MIMO) communication systems. However, these techniques require a high computational complexity since it is required to compute the soft decisions for each bit. In this paper, we show IDD comprised of sphere decoder with low-density parity check (LDPC) codes and present the tree search strategy, called a layer symbol search (LSS), to obtain soft decisions with a low computational complexity. In addition, an adaptive early termination is proposed to reduce the computational complexity during an iteration between an inner sphere decoder and an outer LDPC decoder. It is shown that the proposed approach can achieve the performance similar to an existing algorithm with 70% lower computational complexity compared to the conventional algorithms.