Dissertations / Theses on the topic 'Transportation Network analysis (Planning) Mathematical optimization'

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1

Guan, Junfei. "Simultaneous optimization of transit line configuration and passenger line assignment /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202004%20GUAN.

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2

Yim, Ka-wing, and 嚴家榮. "A reliability-based land use and transportation optimization model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B34618879.

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3

Wang, Shentao. "Supply chain planning using network flow optimization." online access from Digital Dissertation Consortium access full-text, 2003. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?MQ89164.

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4

Yim, Ka-wing. "A reliability-based land use and transportation optimization model." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B34618879.

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5

Hojnacki, Susan M. "Optimizing algorithms for shortest path analysis /." Online version of thesis, 1991. http://hdl.handle.net/1850/11143.

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6

Haiba, Mohamed Salem. "A study and implementation of the network flow problem and edge integrity of networks." Virtual Press, 1991. http://liblink.bsu.edu/uhtbin/catkey/834644.

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Fundamental problems in graph theory are of four types existence, construction, enumeration and optimization problems. Optimization problems lie at the interface between computer science and the field of operations research and are of primary importance in decision-making. In this thesis, two optimization problems are studied: the edge-integrity of networks and the network flow problem. An implementation of the corresponding algorithms is also realized.The edge integrity of a communication network provides a way to assess the vulnerability of the network to disruption through the destruction or failure of some of its links. While the computation of the edge-integrity of graphs in general has been proven to be NPcomplete, a recently published paper was devoted to a good algorithm using a technique of edge separation sequence for computing the edge integrity of trees. The main results of this paper will be presented and an implementation of this algorithm is achieved.The network flow problem models a distribution system in which commodities are flowing through an interconnected network. The goal is to find a maximum feasible flow and its value, given the capacity constraints for each edge. The three majors algorithms for this problem (Ford -Fulkerso n, Edmonds-Karp method, MPKM algorithm) are discussed, their complexities compared and an implementation of the Ford-Fulkerson and the MPKM algorithms is presented.
Department of Computer Science
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7

Brayman, Vladimir. "Hierarchical distributed algorithm for optimization of flows and prices in logistics distribution networks /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/5876.

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8

Boginski, Vladimir L. "Optimization and information retrieval techniques for complex networks." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0011379.

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9

Wong, Chi-Fai. "CACAO : client-assisted channel assignment optimization for uncoordinated home WLANs /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?CSED%202007%20WONG.

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10

Wan, Yen-Tai. "Material transport system design in manufacturing." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-03282006-231022/.

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Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2006.
Dr. Yih-Long Chang, Committee Member ; Dr. Martin Savelsbergh, Committee Member ; Dr. Leon McGinnis, Committee Co-Chair ; Dr. Gunter Sharp, Committee Chair ; Dr. Doug Bodner, Committee Member ; Dr. Joel Sokol, Committee Member.
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11

"Time-varying network optimization problems." 1999. http://library.cuhk.edu.hk/record=b6073189.

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Dan Sha.
Thesis (Ph.D.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (p. 193-206).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Mode of access: World Wide Web.
Abstracts in English and Chinese.
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12

Pan, Feng. "Stochastic network interdiction models and methods /." Thesis, 2005. http://repositories.lib.utexas.edu/bitstream/handle/2152/1692/panf72229.pdf.

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13

Fan, Wei 1974. "Optimal transit route network design problem : algorithms, implementations, and numerical results." 2004. http://hdl.handle.net/2152/12769.

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14

Fan, Wei Machemehl Randy B. "Optimal transit route network design problem algorithms, implementations, and numerical results /." 2004. http://wwwlib.umi.com/cr/utexas/fullcit?p3143741.

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15

Abdelghany, Khaled Faissal Said 1970. "Stochastic dynamic traffic assignment for intermodal transportation networks with consistent information supply strategies." 2001. http://hdl.handle.net/2152/10461.

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16

Marcon, Alister Justin. "Flows in networks : an algorithmic approach." Thesis, 2013. http://hdl.handle.net/10210/8364.

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M.Sc. (Mathematics)
In Chapter 1, we consider the relevant theory pertaining to graphs and digraphs that will be used in the study of flows in networks. Warshall’s algorithm for reachability is also considered since it will allow us to ascertain whether some paths exist in some instance. In Chapter 2, we explore flows and cuts in networks. We define the basic concepts of source, sink, intermediate vertices, capacity, costs and lower-bounds. Feasible flows are defined, as well as the value of a flow. Cuts in capacitated networks are explored and further theory relating the value of a flow and cuts is given. We considered the problem of determining a maximal flow. In particular, we consider augmentations of the flow—this allows us to give a characterization of a maximal flow. The important Max-flow Min-cut theorem is also considered. After having explored the relevant theory, we move on to methods of finding a maximal flow for a given s-t network that has a capacity on each of its arcs. Firstly, we consider zero-one and unit-capacity networks since these play a role in the applications of maximal flows in Chapter 4. We, then, compile the relevant theory and algorithms in order to implement two augmenting path finding algorithms.
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17

Singh, Vidya Bhushan. "User Modeling and Optimization for Environmental Planning System Design." Thesis, 2014. http://hdl.handle.net/1805/6114.

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Indiana University-Purdue University Indianapolis (IUPUI)
Environmental planning is very cumbersome work for environmentalists, government agencies like USDA and NRCS, and farmers. There are a number of conflicts and issues involved in such a decision making process. This research is based on the work to provide a common platform for environmental planning called WRESTORE (Watershed Restoration using Spatio-Temporal Optimization of Resources). We have designed a system that can be used to provide the best management practices for environmental planning. A distributed system was designed to combine high performance computing power of clusters/supercomputers in running various environmental model simulations. The system is designed to be a multi-user system just like a multi-user operating system. A number of stakeholders can log-on and run environmental model simulations simultaneously, seamlessly collaborate, and make collective judgments by visualizing their landscapes. In the research, we identified challenges in running such a system and proposed various solutions. One challenge was the lack of fast optimization algorithm. In our research, several algorithms are utilized such as Genetic Algorithm (GA) and Learning Automaton (LA). However, the criticism is that LA has a slow rate of convergence and that both LA and GA have the problem of getting stuck in local optima. We tried to solve the multi-objective problems using LA in batch mode to make the learning faster and accurate. The problems where the evaluation of the fitness functions for optimization is a bottleneck, like running environmental model simulation, evaluation of a number of such models in parallel can give considerable speed-up. In the multi-objective LA, different weight pair solutions were evaluated independently. We created their parallel versions to make them practically faster in computation. Additionally, we extended the parallelism concept with the batch mode learning. Another challenge we faced was in User Modeling. There are a number of User Modeling techniques available. Selection of the best user modeling technique is a hard problem. In this research, we modeled user's preferences and search criteria using an ANN (Artificial Neural Network). Training an ANN with limited data is not always feasible. There are many situations where a simple modeling technique works better if the learning data set is small. We formulated ways to fine tune the ANN in case of limited data and also introduced the concept of Deep Learning in User Modeling for environmental planning system.
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