• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.465-468
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• 1996

We deal with facility layout problems with shape constraints. A simulated annealing algorithm is developed for the problems. In the algorithm, a solution is encoded as a matrix that has information about relative locations of the facilities in the floor. A block layout is constructed by partitioning the floor into a set of rectangular blocks according to the information while satisfying areas of facilities. In this paper, three methods are suggested for the partitioning procedure and they are employed in the simulated annealing algorithm. Results of computational experiments show that the proposed algorithm performs better than existing algorithms, especially for problems with tight shape constraints.

• Journal of the Korea Society for Simulation
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• v.6 no.1
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• pp.1-13
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• 1997

In this paper, we present a partitioning algorithm for distributed simulation of DEVS (Discrete Event System Specification) models. To preserve concurrency inherent in models, the proposed algorithm utilizes the structural information of models. Through benchmark simulation experiments, we show that the proposed algorithm can generate good partitions.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.6
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• pp.94-104
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• 1984

Based on a new concept of connection index of a weighted graph, a new efficient houris tic algorithm of 0(v.e) for network partitioning is presented, where v and e are the number of nodes and edges, respectively. Experimental results show that our algorithm is very efficient and yields an optimal or near optimal solution for a number of partitioning problems tested. Some applications of the proposed algorithm are suggested and its computer implementation is described in detail.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.11-19
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• 2013

In this paper we present a reodered simulated-anealing algorithm which is capable of applying odering based k-way partitioned clusters. This method is used for improvement of the objectives of partitioning which are k-way partitioned by using odering algorithm. It changes the positions of the clusters and the vertices in each clusters. Reodered vertices are splitted by using DP-RP method and this process has an opportunity to improve the objective functions. This algorithm has advantages to improve the quality of the solutions for various purposes. Experimental results on several graphs demonstrate that proposed algorithm provides substantial enhancement.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1279-1287
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• 2006

The purpose of this paper is to present a new algorithm for extracting the consensus pattern, or motif from sequence belonging to the same family. Two methods are considered for feature interval partitioning based on equal probability and equal width interval partitioning. C2H2 zinc finger protein and epidermal growth factor protein sequences are used to demonstrate the effectiveness of the proposed algorithm for motif extraction. For two protein families, the equal width interval partitioning method performs better than the equal probability interval partitioning method.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.4
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• pp.85-92
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• 1995

A new partitioning algorithm has been developed to implement a large circuit by using multiple field programmable gate array (FPGA) chips. While the conventional partitioning is to minimze the number of nets cut under size constraints, partitioning for multiple FPGAs has several additional constraints so that each partitioned subcircuit can be implemented in a FPGA chip. To obtain satisfactory results under the constraints, the partitioning is performed in two steps whhich are the intial partitioning for global optimization and the iterative partitioning improvements for constraint satisfaction. Experismental results using the MCNC benchmark examples show that our partition method produces better results thatn those of other recent approaches on the average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4347-4366
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• 2015

Distinguished with traditional strategies which offload an application's computation to a single server, parallel computation offloading can promote the performance by simultaneously delivering the computation to multiple computing resources around the mobile terminal. However, due to the variability of communication and computation environments, static application component multi-partitioning algorithms are difficult to maintain the optimality of their solutions in time-varying scenarios, whereas, over-frequent algorithm executions triggered by changes of environments may bring excessive algorithm costs. To this end, an adaptive application component mapping algorithm for parallel computation offloading in variable environments is proposed in this paper, which aims at minimizing computation costs and inter-resource communication costs. It can provide the terminal a suitable solution for the current environment with a low incremental algorithm cost. We represent the application component multi-partitioning problem as a graph mapping model, then convert it into a pathfinding problem. A genetic algorithm enhanced by an elite-based immigrants mechanism is designed to obtain the solution adaptively, which can dynamically adjust the precision of the solution and boost the searching speed as transmission and processing speeds change. Simulation results demonstrate that our algorithm can promote the performance efficiently, and it is superior to the traditional approaches under variable environments to a large extent.

• Journal of the Korean Society for Railway
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• v.7 no.4
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• pp.326-331
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• 2004

A routing is the path that an actual trainset follows as it moves from one train to another train in a timetable. The number of routings is equivalent to the number of trainsets required to cover the timetable. The primary factors of rolling stock requirement plan include evaluating the minimum number of routings. This can be formulated as a set partitioning problem and solved using enumeration method or column generation method. In this paper we presents an enumeration algorithm which is useful to implement the enumeration method for the rolling stock requirement plan.

• Journal of Korea Game Society
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• v.9 no.2
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• pp.115-123
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• 2009

This paper proposes an algorithm to improve the performance of the spatial partitioning method for flocking behaviors. The core concept is to improve the performance by using the fact that even if a moving entity, boid in flock continuously changes its direction and position, its k-nearest neighbors, kNN to effect on decision of the next direction is not changed frequently. From the previous kNN, the method to check whether new kNN is changed or not is proposed in this paper and then the correctness of the proposed method is proved by two theorems. The proposed algorithm was implemented and its performance was compared with the conventional spatial partitioning method. The results of the comparison show that the proposed algorithm outperforms the conventional one by about 30% with respect to the number of frames per a second.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5244-5259
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• 2019

With the continuous development of LBS (Location Based Service) applications, privacy protection has become an urgent problem to be solved. Differential privacy technology is based on strict mathematical theory that provides strong privacy guarantees where it supposes that the attacker has the worst-case background knowledge and that knowledge has been applied to different research directions such as data query, release, and mining. The difficulty of this research is how to ensure data availability while protecting privacy. Spatial multidimensional data are usually released by partitioning the domain into disjointed subsets, then generating a hierarchical index. The traditional data-dependent partition methods need to allocate a part of the privacy budgets for the partitioning process and split the budget among all the steps, which is inefficient. To address such issues, a novel two-step partition algorithm is proposed. First, we partition the original dataset into fixed grids, inject noise and synthesize a dataset according to the noisy count. Second, we perform IH-Tree (Improved H-Tree) partition on the synthetic dataset and use the resulting partition keys to split the original dataset. The algorithm can save the privacy budget allocated to the partitioning process and obtain a more accurate release. The algorithm has been tested on three real-world datasets and compares the accuracy with the state-of-the-art algorithms. The experimental results show that the relative errors of the range query are considerably reduced, especially on the large scale dataset.