Leung, Ka Lun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 118-126). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Constraint Satisfaction and Global Constraints --- p.3 / Chapter 1.2 --- Soft Constraints --- p.4 / Chapter 1.3 --- Motivation and Goal --- p.5 / Chapter 1.4 --- Outline of the Thesis --- p.6 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Constraint Satisfaction Problems --- p.8 / Chapter 2.1.1 --- Backtracking Tree Search --- p.10 / Chapter 2.1.2 --- Local Consistency in CSP --- p.11 / Chapter 2.1.3 --- Constraint Optimization Problem --- p.16 / Chapter 2.2 --- Weighted Constraint Satisfaction --- p.21 / Chapter 2.2.1 --- Branch and Bound Search --- p.23 / Chapter 2.2.2 --- Local Consistency in WCSP --- p.26 / Chapter 2.3 --- Global Constraints --- p.35 / Chapter 2.4 --- Flow Theory --- p.37 / Chapter 3 --- Related Work --- p.39 / Chapter 3.1 --- Handling Soft Constraints in COPs --- p.39 / Chapter 3.2 --- Global Constraints --- p.40 / Chapter 3.2.1 --- Hard Global Constraints --- p.40 / Chapter 3.2.2 --- Soft Global Constraints --- p.41 / Chapter 3.3 --- Local Consistency in Weighted CSP --- p.42 / Chapter 4 --- “Soft as Hard´ح Approach --- p.44 / Chapter 4.1 --- The General “Soft as Hard´ح Approach --- p.44 / Chapter 4.2 --- Cost-based GAC --- p.49 / Chapter 4.3 --- Empirical Results --- p.53 / Chapter 5 --- Weighted CSP Approach --- p.55 / Chapter 5.1 --- Strong 0-Inverse Consistency --- p.55 / Chapter 5.1.1 --- 0-Inverse Consistency and Strong 0-Inverse Consistency --- p.56 / Chapter 5.1.2 --- Comparison with Other Consistencies --- p.62 / Chapter 5.2 --- Generalized Arc Consistency Star --- p.65 / Chapter 5.3 --- Full Directional Generalized Arc Consistency Star --- p.72 / Chapter 5.4 --- Generalizing EDAC* --- p.78 / Chapter 5.5 --- Implementation Issues --- p.87 / Chapter 6 --- Towards A Library of Efficient Soft Global Constraints --- p.90 / Chapter 6.1 --- The allDifferent Constraint --- p.91 / Chapter 6.1.1 --- All Interval Series --- p.93 / Chapter 6.1.2 --- Latin Square --- p.95 / Chapter 6.2 --- The GCC Constraint --- p.97 / Chapter 6.2.1 --- Latin Square --- p.100 / Chapter 6.2.2 --- Round Robin Tournament --- p.100 / Chapter 6.3 --- The Same Constraint --- p.102 / Chapter 6.3.1 --- Fair Scheduling --- p.104 / Chapter 6.3.2 --- People-Mission Scheduling --- p.105 / Chapter 6.4 --- The Regular Constraint --- p.106 / Chapter 6.4.1 --- Nurse Rostering Problem --- p.110 / Chapter 6.4.2 --- Modelling Stretch() Constraint --- p.111 / Chapter 6.5 --- Discussion --- p.113 / Chapter 7 --- Conclusion and Remarks --- p.115 / Chapter 7.1 --- Contributions --- p.115 / Chapter 7.2 --- Future Work --- p.117 / Bibliography --- p.118

Thesis (Ph.D.)--University of Delaware, 2009. / Principal faculty advisor: Keith S. Decker, Dept. of Computer & Information Sciences. Includes bibliographical references.

Jiang, Kening. / "August 2011." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 90-93). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Portfolio Selection Using Clustering Methodology --- p.7 / Chapter 2.1 --- Heuristic algorithm --- p.8 / Chapter 2.1.1 --- Step 1: Security transformation by factor model --- p.8 / Chapter 2.1.2 --- Step 2: Clustering algorithm --- p.10 / Chapter 2.1.3 --- Step 3: Representative selection by t he Sliarpe ratio --- p.16 / Chapter 2.2 --- Numerical results --- p.17 / Chapter 3 --- Modified Portfolio Selection Using Clustering Methodology --- p.22 / Chapter 3.1 --- Analysis of artificial factors --- p.23 / Chapter 3.2 --- Problem reformulation --- p.27 / Chapter 3.3 --- Numerical results --- p.29 / Chapter 4 --- Minimum Variance Point --- p.70 / Chapter 4.1 --- Iterative elimination scheme I --- p.72 / Chapter 4.2 --- Iterative elimination scheme II --- p.74 / Chapter 4.3 --- Orthogonal matrix mapping --- p.76 / Chapter 4.4 --- Condition to solve diagonal dominant problem --- p.77 / Chapter 4.5 --- L1 formulation --- p.82 / Chapter 4.6 --- Numerical results --- p.85 / Chapter 5 --- Summary and Future work --- p.88

Optical signal-to-noise ratio (OSNR) is considered as the dominant performance parameter at the physical layer in optical networks. This thesis is interested in control and optimization of channel OSNR by using optimization and game-theoretic approaches, incorporating two physical constraints: the link capacity constraint and the channel OSNR target. To start, we study OSNR optimization problems with link capacity constraints in single point-to-point fiber links via two approaches. We first present a framework of a Nash game between channels towards optimizing individual channel OSNR. The link capacity constraint is imposed as a penalty term to each cost function. The selfish behavior in a Nash game degrades the system performance and leads to the inefficiency of Nash equilibria. From the system point of view, we formulate a system optimization problem with the objectives of achieving an OSNR target for each channel while satisfying the link capacity constraint. As an alternative to study the efficiency of Nash equilibria, we use the system framework to investigate the effects of parameters in cost functions in the game-theoretic framework. Then extensions to multi-link and mesh topologies are carried out. We propose a partition approach by using the flexibility of channel power adjustment at optical switches. The multi-link structure is partitioned into stages with each stage being a single sink. By fully using the flexibility, a more natural partition approach is applied to mesh topologies where each stage is a single link. The closed loop in mesh topologies can be unfolded by selecting a starting link. Thus instead of maximization of channel OSNR from end to end, we consider minimization of channel OSNR degradation between stages. We formulate a partitioned Nash game which is composed of ladder-nested stage Nash games. Distributed algorithms towards the computation of a Nash equilibrium solution are developed for all different game frameworks. Simulations and experimental implementations provide results to validate the applicability of theoretical results.

Optical signal-to-noise ratio (OSNR) is considered as the dominant performance parameter at the physical layer in optical networks. This thesis is interested in control and optimization of channel OSNR by using optimization and game-theoretic approaches, incorporating two physical constraints: the link capacity constraint and the channel OSNR target. To start, we study OSNR optimization problems with link capacity constraints in single point-to-point fiber links via two approaches. We first present a framework of a Nash game between channels towards optimizing individual channel OSNR. The link capacity constraint is imposed as a penalty term to each cost function. The selfish behavior in a Nash game degrades the system performance and leads to the inefficiency of Nash equilibria. From the system point of view, we formulate a system optimization problem with the objectives of achieving an OSNR target for each channel while satisfying the link capacity constraint. As an alternative to study the efficiency of Nash equilibria, we use the system framework to investigate the effects of parameters in cost functions in the game-theoretic framework. Then extensions to multi-link and mesh topologies are carried out. We propose a partition approach by using the flexibility of channel power adjustment at optical switches. The multi-link structure is partitioned into stages with each stage being a single sink. By fully using the flexibility, a more natural partition approach is applied to mesh topologies where each stage is a single link. The closed loop in mesh topologies can be unfolded by selecting a starting link. Thus instead of maximization of channel OSNR from end to end, we consider minimization of channel OSNR degradation between stages. We formulate a partitioned Nash game which is composed of ladder-nested stage Nash games. Distributed algorithms towards the computation of a Nash equilibrium solution are developed for all different game frameworks. Simulations and experimental implementations provide results to validate the applicability of theoretical results.

No description available.

No description available.

The primary aim of this study is to assess the applicability and performance of the finite element method (FEM) in solving structural optimization problems with stability constraints. In order to reach this goal, several optimization problems are solved using FEM which are briefly described as follows: The strongest column problem is one of the oldest optimization problems for which analytical solutions exist only for some special cases. Here, both unimodal and bimodal optimization of columns under concentrated and/or distributed compressive loads with several different boundary conditions and constraints are performed using an iterative method based on finite elements. The analytical solutions available in the literature for columns under concentrated loads and an analytical solution derived for simply supported columns under distributed loads are used for verification purposes. Optimization results are presented for fibre-reinforced composite rectangular plates under inplane loads. The non-uniformity of the in-plane stresses due to stress diffusion and/or in-plane boundary conditions is taken into account, and its influence on optimal buckling load is investigated. It is shown that the exclusion of the in-plane restraints may lead to errors in stability calculations and consequently in optimal design. The influences of the panel aspect ratio, stacking sequence, panel thickness, and the rotational edge restraints on the optimal axially compressed cylindrical and non-cylindrical curved panels are investigated, where the optimal panel is the one with the highest failure load. The prebuckling and the first-ply failure loads of the panels are calculated and minimum of these two is selected as the failure load. The results show that there are distinct differences between the behaviour of cylindrical and non-cylindrical panels. The formulations of the finite elements which are used throughout the study are given and several verification problems are solved to verify the accuracy of the methodology. The computer codes written in Matlab are also given in the appendix sections accompanied with the selected codes used for optimization purposes. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2006.

Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 62-64). Also available on the World Wide Web.

The focus of Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) research is to develop a system to avoid situations in which the vehicle exceeds its handling capabilities. The proposed method is predictive, estimating the ability of the vehicle to successfully navigate upcoming terrain, and it is assumed that the future vehicle states and local driving environment is known. An Intervention Strategy must be developed such that the vehicle is navigated successfully along a road via modest changes to the driver's commands and do so in a manner that is in harmony with the driver's intentions and not in a distracting or irritating manner. Clearly this research relies on the numerous new technologies being developed to capture and convey information about the local driving environment (e.g., bank angle, elevation changes, curvature, and friction coefficient) to the vehicle and driver. / Ph. D.