Browsing by Author "Hsu, Chia-Chun"

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A genetic algorithm for the maximum edge-disjoint paths problem
(2015-01-19)
Hsu, Chia-Chun
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Cho, Hsun-Jung
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Optimization problems concerning edge-disjoint paths have attracted considerable attention for decades. These problems have a lot of applications in the areas of call admission control, real-time communication, VLSI (Very-large-scale integration) layout and reconfiguration, packing, etc. The maximum edge-disjoint paths problem (MEDP) seems to lie in the heart of these problems. Given an undirected graph G and a set of I connection requests, each request consists of a pair of nodes, MEDP is an NP-hard problem which determines the maximum number of accepted requests that can be routed by mutually edge-disjoint (s(i),t(i)) paths. We propose a genetic algorithm (GA) to solve the problem. In comparison to the multi-start simple greedy algorithm (MSGA) and the ant colony optimization method (ACO), the proposed GA method performs better in most of the instances in terms of solution quality and time. (C) 2014 Elsevier B.V. All rights reserved.
Method for identification of traffic lane boundary
(2010-06-24)
Jou, Yow-Jen
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Cho, Hsun-Jung
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Chen, Yu-Kuang
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Huang, Heng
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Hsu, Chia-Chun
The invention provides a method for identification of traffic lane boundary. Firstly the microwave signal is received, and the noise reduction is treated for the microwave signal. Then the frequency domain information is employed to calculate the legal set of closed interval, in order to form the frequency span information. Finally, the probability density function model is employed to calculate the frequency span information in order to identify the traffic lane boundary.
Parallel chain convergence of time dependent origin-destination matrices with gibbs sampler
(2006)
Jou, Yow-Jen
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Ch, Hsun-Jung
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Lan, Chien-Lun
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Hsu, Chia-Chun
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資訊管理與財務金融系註：原資管所+財金所
An effective method of O-D estimation by the state-space model has been introduced by Jon. Coupled with Gibbs sampler and Kalman filter, the state-space model can generated precious O-D matrices without any prior information while other studies assume that the transition matrix is known or at least approximately known. The Gibbs sampler, a particular type of Markov Chain Monte Carlo method, is one of the iterative simulation methods. To monitor of convergence of this iterative simulation, a parallel chain technique is implemented in this paper. By the numerical example, the convergence of the different chains would be clearly pointed out. The comparison of simulation and real data also shows that satisfying results can be obtained by the model.
SOLVING ROUTING AND WAVELENGTH ASSIGNMENT PROBLEM WITH MAXIMUM EDGE-DISJOINT PATHS
(2017-04-01)
Hsu, Chia-Chun
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Cho, Hsun-Jung
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Fang, Shu-Cherng
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
The routing and wavelength assignment (RWA) problem in wavelength-division multiplexing optical networks is critically important for increasing the efficiency of wavelength-routed all-optical networks. Given the physical network structure and a set of connection requests, the problem aims to establishing routes for the requests and assigning a wavelength to each of them, subject to the wavelength continuous and wavelength clash constraints. The objective is to minimize he number of required wavelengths to satisfy all requests. The RWA problem was proven to be NP-hard and has been investigated for decades. In this paper, an algorithm based on the maximum edge-disjoint paths is proposed to tackle the RWA problem. Its performance is verified by experiments on some realistic network topologies. Compared with the state-of-the-art bin-packing based methods and the particle swarm optimization al- gorithm, the proposed method can find the best solution among all testing instances in reasonable computing time.