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41 
Efficient implementations of the primaldual methodOsiakwan, Constantine N. K. January 1984 (has links)
No description available.

42 
A survey of the most recent stateofthe art shortest path algorithms and their applications to different types of networks.Comninos, Gerry January 1991 (has links)
This research report is submitted to the Faculty of Science, University of the
Witwatersrand, Johannesburg, in part fulfillment of the requirements for the
degree of Master of Science / The title of this research report is a "A Survey of the most recent State
oftheArt Shortest path algorithms"
One may ask what is the need and aim of this survey. During the decades
of the 1970's and 1980's there has been considerable research and publication
in shortest path algorithm. Each new publication is either a new
and faster algorithm or survey of recent methods. ( Abbreviation abstract ) / AC2017

43 
A Graphonbased Framework for Modeling Large NetworksHe, Ran January 2015 (has links)
This thesis focuses on a new graphonbased approach for fitting models to large networks and establishes a general framework for incorporating nodal attributes to modeling. The scale of network data nowadays, renders classical network modeling and inference inappropriate. Novel modeling strategies are required as well as estimation methods.
Depending on whether the model structure is specified a priori or solely determined from data, existing models for networks can be classified as parametric and nonparametric. Compared to the former, a nonparametric model often allows for an easier and more straightforward estimation procedure of the network structure. On the other hand, the connectivities and dynamics of networks fitted by nonparametric models can be quite difficult to interpret, as compared to parametric models.
In this thesis, we first propose a computational estimation procedure for a class of parametric models that are among the most widely used models for networks, built upon tools from nonparametric models with practical innovations that make it efficient and capable of scaling to large networks.
Extensions of this base method are then considered in two directions. Inspired by a popular network sampling method, we further propose an estimation algorithm using sampled data, in order to circumvent the practical obstacle that the entire network data is hard to obtain and analyze. The base algorithm is also generalized to consider the case of complex network structure where nodal attributes are involved. Two general frameworks of a nonparametric model are proposed in order to incorporate nodal impact, one with a hierarchical structure, and the other employs similarity measures.
Several simulation studies are carried out to illustrate the improved performance of our proposed methods over existing algorithms. The proposed methods are also applied to several real data sets, including Slashdot online social networks and inschool friendship networks from the National Longitudinal Study of Adolescent to Adult Health (AddHealth Study). An array of graphical visualizations and quantitative diagnostic tools, which are specifically designed for the evaluation of goodness of fit for network models, are developed and illustrated with these data sets. Some observations of using these tools via our algorithms are also examined and discussed.

44 
Operationalising dynamic capabilities : a supply network configuration approachAlinaghian, Leila Sadat January 2015 (has links)
No description available.

45 
A simplex based computational procedure for the maximal multitransformed network flows problem /Mavrogenis, Paris. January 1975 (has links)
No description available.

46 
Minimal cost flows in networks with transformations, byproducts, convex and concave costsEmmanuelidis, John A. January 1975 (has links)
No description available.

47 
An investigation into the behaviour of teletraffic networks in whichi several streams are offered to a common link, with particular attention to partitioning of the overflow streamWilson, Kym Graham January 1977 (has links)
iii, 122 leaves : ill., tables ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)University of Adelaide, Dept. of Applied Mathematics, 1977

48 
A mathematical model for the longterm planning of a telephone networkBruyn, Stewart James January 1977 (has links)
69 leaves : tables ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)University of Adelaide, Dept. of Applied Mathematics, 1979

49 
Supply chain planning using network flow optimizationWang, Shentao. January 2003 (has links) (PDF)
Thesis (master's)Dalhousie University (Canada), 2003. / Adviser: Uday Venkatadri. Includes bibliographical references.

50 
Network models with generalized upper bound side constraintsBolouri, Maryam 27 July 1989 (has links)
The objective of this thesis is to develop and
computationally test a new algorithm for the class of
network models with generalized upper bound (GUB) side
constraints. Various algorithms have been developed to
solve the network with arbitrary side constraints problem;
however, no algorithm that exploits the special structure
of the GUB side constraints previously existed. The
proposed algorithm solves the network with GUB side
constraints problem using two sequences of problems. One
sequence yields a lower bound on the optimal value for the
problem by using a Lagrangean relaxation based on relaxing
copies of some subset of the original variables. This is
achieved by first solving a pure network subproblem and
then solving a set of single constraint bounded variable
linear programs. Because only the cost coefficients
change from one pure network subproblem to another, the
optimal solution for one subproblem is at least feasible,
if not optimal, for the next pure network subproblem. The
second sequence yields an upper bound on the optimal value
by using a decomposition of the problem based on changes
in the capacity vector. Solving for the decomposed
problem corresponds to solving for pure network
subproblems that have undergone changes in lower and/or
upper bounds. Recently developed reoptimization
techniques are incorporated in the algorithm to find an
initial (artificial) feasible solution to the pure network
subproblem.
A program is developed for solving the network with
GUB side constraints problem by using the relaxation and
decomposition techniques. The algorithm has been tested
on problems with up to 200 nodes, 2000 arcs and 100 GUB
constraints. Computational experience indicates that the
upper bound procedure seems to perform well; however, the
lower bound procedure has a fairly slow convergence rate.
It also indicates that the lower bound step size, the
initial lower bound value, and the lower and upper bound
iteration strategies have a significant effect on the
convergence rate of the lower bound algorithm. / Graduation date: 1990

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