• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.2
• /
• pp.22-30
• /
• 2023

The portable mobile devices with high performance and high speed 5G network activate and explode the demands for ubiquitous information services that remove the limitations of time for the communication and places to request for the information. NN (Nearest Neighbor) search is one of the most important types of queries to be processed efficiently in the information services. Various indexes have been proposed to support efficient NN search in the wireless broadcast system. The indexes adopting Hilbert curve, grid partition or Voronoi diagram enable the clients to search for NN quickly in the wireless broadcast channel. It is necessary that an efficient means to evaluate the performances of various indexes. In this paper, we propose an open framework that can adopt a variety of indexing schemes and evaluate and compare the performances of them. The proposed framework is organized with open and flexible structure that can adopt hybrid indexing schemes extensible to Voronoi diagram as well as simple indexing schemes. With the implemented framework, we demonstrate the efficiency and scalability and flexibility of the proposed framework by evaluating various indexing schemes for NN query.

• Smart Structures and Systems
• /
• v.26 no.3
• /
• pp.345-360
• /
• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• Geomechanics and Engineering
• /
• v.1 no.1
• /
• pp.85-96
• /
• 2009

The radius and coordinate of sliding circle are taken as searching variables in slope stability analysis. Genetic algorithm is applied for searching for critical factor of safety. In order to search for critical factor of safety in slope stability analysis efficiently and in a robust manner, some improvements for simple genetic algorithm are proposed. Taking the advantages of efficiency of neighbor-search of the simulated annealing and the robustness of genetic algorithm, a hybrid optimization method is presented. The numerical computation shows that the procedure can determine the minimal factor of safety and be applied to slopes with any geometry, layering, pore pressure and external load distribution. The comparisons demonstrate that the genetic algorithm provides a same solution when compared with elasto-plastic finite element program.

• ETRI Journal
• /
• v.43 no.2
• /
• pp.260-271
• /
• 2021

This paper addresses Very large-scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such as random forest, hill climbing, and variable neighborhoods, can be effectively applied to NP-hard problem-solving. They provide improved solutions, which are obtained after a global search. The scientific novelty of this research is based on the development of systems, principles, and methods for creating a hybrid (combined) placement algorithm. The principal difference in the proposed algorithm is that it obtains a set of alternative solutions in parallel and then selects the best one. Nonstandard genetic operators, based on problem knowledge, are used in the proposed algorithm. An investigational study shows an objective-function improvement of 13%. The time complexity of the hybrid placement algorithm is O(N2).

• Journal of the Korean Society for Library and Information Science
• /
• v.49 no.4
• /
• pp.203-220
• /
• 2015

This study was to suggest the creation of hybrid bibliographic records in complicated bibliographic environment applying both AACR2 and RDA for uniform display and correct search. The literature reviews and case studies were used as the research methods. In case studies, Kent State University, University of Houston as the libraries, and Backstage Library Works as algorithm converting to hybrid records were surveyed. For creating the hybrid records, it was needed to differentiate hybrid records and born RDA records, to keep the data that appeared in 250 tag without spelling out edition data, to maintain 260 tag instead of converting 260 tag to 264 tag, and last to design mapping table for converting GMD to CMC. This study would suggest uniform display and search through hybridization of bibliographic records of foreign resources.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.61-73
• /
• 2021

Metaheuristic search methods have been developed to solve problems with a range of purpose functions in situations lacking information and time constraints. In this study, the Hybrid Vision Correction Algorithm (HVCA), which enhances the performance of the Vision Correction Algorithm (VCA), was developed. The HVCA has applied two methods to improve the performance of VCA. The first method changes the parameters required by the user for self-adaptive parameters. The second method, the CGS structure of the Exponential Bandwidth Harmony Search With a Centralized Global Search (EBHS-CGS), was added to the HVCA. The HVCA consists of two structures: CGS and VCA. To use the two structures, a method was applied to increase the probability of selecting the structure with the optimal value as it was performed. The optimization problem was applied to determine the performance of the HVCA, and the results were compared with Harmony Search (HS), Improved Harmony Search (IHS), and VCA. The HVCA improved the number of times to find the optimal value during 100 repetitions compared to HS, IHS, and VCA. Moreover, the HVCA reduced the Number of Function Evaluations (NFEs). Therefore, the performance of the HVCA has been improved.

• Journal of Korean Institute of Industrial Engineers
• /
• v.33 no.1
• /
• pp.86-98
• /
• 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.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.28A no.11
• /
• pp.855-865
• /
• 1991

A simple method for analysis of serial search burst-format direct-sequence spread-spectrum (DS-SS) code acquisition system had been recently proposed, and therein, the effect of the code autocorrelation sidelobes on the performance of DS-SS code acquisition system has been assessed [4],[5]. In this paper, a new hybrid scheme which combines the serial search with maximum likelihood search is proposed to eliminate the deleterious effect of code autocorrelation sidelobes, and the performance is analyzed for the additive withe Gaussian noise (AWGN) channels. To analyze the performance of this system, we have generalized the method used in [4],[5] to arbitrary burst-format DS-SS acquisition schemes. The results show that a new hybrid scheme has good immunity against the effect of code autocorrelation sidelobes. Thevalidity of the presented approach has been confirmed form the results of simulation.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.24 no.1
• /
• pp.63-68
• /
• 2015

Pattern layout design is very important to the automation of apparel industry. Until now, the genetic algorithm and Tabu search method have been applied to layout design automation. With the genetic algorithm and Tabu search method, the obtained values are not always consistent depending on the initial conditions, number of iterations, and scheduling. In addition, the selection of various parameters for these methods is not easy. This paper presents a hybrid search method that uses a neural network and simulated annealing to solve these problems. The layout of pattern elements was optimized to verify the potential application of the suggested method to apparel pattern layout design.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.6
• /
• pp.686-691
• /
• 2011

This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.