Thesis--Wisconsin. / Vita. Includes bibliographical references (leaves 145-147).

The problems involved in network planning for project control are examined with reference to the published work in this field. Various solutions are described and compared. A detailed investigation is made of the standard assumptions concerning expected activity durations. The different approaches to the estimation of these times are shown to be inconsistent with their areas of application. A global heuristic solution to the problem of finding the minimum value of the maximum resource requirement during a project is presented. This procedure uses a modified resource profile. The results of a comparison between this solution and a standard local solution indicate a slight improvement with a considerable increase in computing time. The new approach permits easier subminimization. A combination of these methods is proposed. / Science, Faculty of / Computer Science, Department of / Graduate

This thesis is concerned with a network design problem which is referred to in the literature as the network synthesis problem. The objective is to design an undirected network, at a minimum cost, which satisfies known requirements, i.e., lower bounds on the maximum flows, between every pair of nodes. If the requirements are to be satisfied nonsimultaneously, i.e., one at a time, the problem is called the nonsimultaneous network synthesis problem, whereas if the requirements are to be satisfied simultaneously, the problem is called the simultaneous network synthesis problem. The total construction cost of the network is the sum of the construction cost of capacities on the edges, where the construction cost of a unit capacity is fixed for any edge, independent of the size of the capacity, but it may differ from edge to edge. The capacities are allowed to assume noninteger nonnegative values. The simultaneous network synthesis problem was efficiently solved by Gomory and Hu [60], whereas the nonsimultaneous network synthesis problem can only be formulated and solved as a linear program with a large number of constraints. However, the special equal-cost case, i.e., when the unit construction costs are equal across the edges, can be efficiently solved, see Gomory and Hu [60], by some combinatorial method, other than linear programming. A cost allocation problem which is associated with the network synthesis problem would naturally arise, if we assume that the various nodes in the network represent different users or communities. In this case, we need to find a fair method for allocating the construction cost of the network among the different users. An interesting generalization of the nonsimultaneous network synthesis problem, the Steiner network synthesis problem, is derived, when only a proper subset of the nodes have positive requirements from each other. The thesis is concerned with two issues. First, we will analyze the cost allocation problems arising in the simultaneous and the equal cost nonsimultaneous network synthesis problem. Secondly, we will consider the Steiner network synthesis problem, with particular emphasis on simplifying the computations in some special cases, not considered before. We will employ cooperative game theory to formulate the cost allocation problems, and we will prove that the derived games are 'concave', which implies the existence of the core and the inclusion of the Shapley value and the nucleolus in the core, and then we will present irredundant representations of the cores. For the equal cost nonsimultaneous network synthesis game, we will use the irredundant representation of the core to provide an explicit closed form expression for the nucleolus of the game, when the requirement structure is a spanning tree; then, we will develop, in a special case, a decomposition of the game, which we will later use to efficiently compute the Shapley value of the game when the requirement structure is a tree; the decomposition will also be used for the core and the nucleolus of the game in the special case. For the simultaneous network synthesis game, we will also use the irredundant representation of the core to derive an explicit closed form expression for the nucleolus, and we will also decompose the core of this game in the special case, and prove that the Shapley value and the nucleolus coincide. Secondly, for the Steiner network synthesis problem, two conceptually different contributions have been made, one being a simplifying transformation, and the other being the case when the network has to be embedded in (i.e., restricted to) some special graphs. Namely, when the requirement structure is sparse (because there are only a few demand nodes and the rest are just intermediate nodes) and the positive requirements are equal, we will employ a transformation procedure to simplify the computations. This will enable us to efficiently solve the Steiner network synthesis problem with five or less nodes which have equal positive requirements from each other. Finally, when the solution network to the Steiner network synthesis problem is to be embedded in (restricted to) some special graphs, namely trees, rings (circles), series-parallel graphs, or M₂ and M₃-free graphs, we will provide combinatorial algorithms which are expected to simplify the computations. / Business, Sauder School of / Graduate

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Li Pingping = 网络的结构性质及其动态过程 / 李萍萍. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 113-118). / Text in English; abstracts in English and Chinese. / Li Pingping = Wang luo de jie gou xing zhi ji qi dong tai guo cheng / Li Pingping. / Chapter 1 --- Overview --- p.1 / Chapter 2 --- Networks: A Review --- p.6 / Chapter 2.1 --- Graph Theory --- p.6 / Chapter 2.1.1 --- Degree --- p.7 / Chapter 2.1.2 --- Shortest-Path Length --- p.7 / Chapter 2.1.3 --- Clustering Coefficient --- p.8 / Chapter 2.2 --- Random Graphs --- p.9 / Chapter 2.2.1 --- Degree Distribution --- p.10 / Chapter 2.2.2 --- Shortest-Path Length --- p.11 / Chapter 2.2.3 --- Clustering Coefficient --- p.11 / Chapter 2.2.4 --- Shortcomings of The Model --- p.12 / Chapter 2.3 --- Small-World Network --- p.14 / Chapter 2.3.1 --- Small-World Effect in Real-World Networks --- p.14 / Chapter 2.3.2 --- Watts-Strogatz Model --- p.16 / Chapter 2.3.3 --- Properties --- p.17 / Chapter 2.3.4 --- Newman-Watts Model --- p.23 / Chapter 2.4 --- Scale-Free Network --- p.24 / Chapter 2.4.1 --- Background --- p.24 / Chapter 2.4.2 --- The Barabasi-Albert Model --- p.25 / Chapter 2.4.3 --- Shortest-Path Length --- p.28 / Chapter 2.4.4 --- Clustering Coefficient --- p.28 / Chapter 2.5 --- Summary --- p.29 / Chapter 3 --- Clustering Coefficient in Complex Networks --- p.30 / Chapter 3.1 --- Introduction --- p.30 / Chapter 3.2 --- Barabasi-Albert Networks --- p.32 / Chapter 3.3 --- Random Growing Networks --- p.37 / Chapter 3.4 --- Hybrid Networks with both Preferential and Random Attachments --- p.40 / Chapter 3.5 --- Summary --- p.42 / Chapter 4 --- Voter Model --- p.44 / Chapter 4.1 --- Introduction --- p.44 / Chapter 4.2 --- Voter Model --- p.45 / Chapter 4.3 --- Conservation Laws --- p.46 / Chapter 4.4 --- Ordering Process on Complex Networks --- p.47 / Chapter 4.5 --- Effective Dimension --- p.51 / Chapter 4.6 --- Summary --- p.52 / Chapter 5 --- Opinion Formation in Newman-Watts Networks --- p.54 / Chapter 5.1 --- Introduction --- p.54 / Chapter 5.2 --- Majority Rule Model in Newman-Watts Networks --- p.56 / Chapter 5.3 --- Shortening of Consensus Time --- p.58 / Chapter 5.4 --- Shortcuts and Mean-Field Limit --- p.61 / Chapter 5.5 --- Consensus Time and Shortest-Path Length --- p.65 / Chapter 5.6 --- Summary --- p.67 / Chapter 6 --- Opinion Formation in Hierarchical Networks --- p.68 / Chapter 6.1 --- Hierarchical Networks --- p.69 / Chapter 6.2 --- Shortest-Path Length --- p.72 / Chapter 6.3 --- Dynamics of Opinion Formation Model --- p.74 / Chapter 6.4 --- Summary --- p.81 / Chapter 7 --- An Introduction to Iterated Games --- p.82 / Chapter 7.1 --- Background --- p.82 / Chapter 7.2 --- Matrix Games --- p.83 / Chapter 7.3 --- The Prisoner's Dilemma --- p.85 / Chapter 7.4 --- Iterated Prisoner's Dilemma --- p.87 / Chapter 7.5 --- Evolutionary Game Theory --- p.90 / Chapter 7.5.1 --- Games in a Well-Mixed Population --- p.91 / Chapter 7.5.2 --- Games in Spatial Structure --- p.92 / Chapter 7.6 --- The Snowdrift Game --- p.92 / Chapter 8 --- Stochastic Reactive Strategies in Infinitely Iterated Games --- p.95 / Chapter 8.1 --- The PD and SD Games --- p.95 / Chapter 8.2 --- Stochastic Reactive Strategies --- p.97 / Chapter 8.3 --- Evolution of Stochastic Strategies --- p.100 / Chapter 8.4 --- Stochastic Strategies in Infinitely IPD --- p.101 / Chapter 8.5 --- Summary --- p.107 / Chapter 9 --- Summary --- p.109 / Bibliography --- p.113

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.

Thesis (M. A.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Thesis (Ph. D.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 141-145).

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