Thesis (Ph. D.)--University of Chicago, Dept. of Economics, June 2000. / Includes bibliographical references. Also available on the Internet.

Thesis (Ph. D.)--New York University, 1996. / Includes bibliographical references (leaves 126-134).

Thesis (M.Arch.)--University of Hong Kong, 1994. / Includes special report study entitled : Urban campus open space. Includes bibliographical references. Also available in print.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references (leaves 42-44). Also available in electronic version.

The quality cost of non-conformance associated with first run production builds is typically more than five times that of later production runs. If a manufacturing organization is to gain market share and increase its profitability, it must explore methods of accelerating its learning curves through defect prevention. Current "Transition to Production" concept methodologies attempt with limited success to accelerate organizational learning through Design for Manufacturability (DFM), design phase dimensional management studies, manufacturing floor statistical methods (SPC, DOE, etc.), and various qualitative strategies. While each of these techniques are effective to some degree in reducing future nonconformances, an integrated, design-phase approach utilizing current technology is needed. "Virtual Process Capability" (VPC) is a methodology for integrating statistical process capability knowledge directly into the hardware design phase, resulting in the improved performance and reduced product costs typically associated with mature product manufacturing. The intent behind the methodology is to realistically simulate the manufacture of hardware products by understanding their underlying model equations and the statistical distributions of each involved contributing parameter. Once each product has been simulated and an expected percentage defective has been estimated, mathematical programming and statistical quality engineering techniques are then utilized for improvement purposes. Data taken from the practical application of this methodology at Raytheon Aircraft has conservatively estimated that for each dollar invested ten are saved. As a technical extension to this developed methodology, statistical insights and methods are provided as to how product and process improvement analysis is best accomplished. Included within this area of discussion is the statistical development and validation of improved measures for the more efficient detection of dispersion and mean effects than that of more traditional methods. Additionally, the use of mathematical programming techniques is creatively employed as an improved mechanism in the optimization of nominal-the-best type problems.

The facility layout problem is modelled as a cycle decomposition process in which the maximum-weight clique and travelling salesman problems are utilized to extract cycles from the graph adjacency matrix. The space between cycles is triangulated so the graph is maximally planar. The adjacency graph is then systematically developed into a block plan layout. With use of the maximum-weight clique algorithm, the procedure addresses layout problems that are not 100% dense. Many examples are utilized to demonstrate the flexibility of the algorithm and the resulting adjacency graph and block plan layout drawings. The Steiner Circulation Network solution derived from an adjacency graph solution and its dual graph, provides a minimum cost system of hallways and connecting links for the material handling system. Using the flows between activities and departments in a layout problem, the circulation network provides the necessary link between the steps of finding the adjacency graph solution and finding useful block plan layout. A case study demonstrates how the solution for the layout and its material handling system can be integrated. Computational results up to size n = 100 are presented along with a comparative study with a competitive algorithm.

In this dissertation, I developed a unified complex network framework for environmental decision-making. I focused on complex network systems arising in the context of green logistics, including global supply chains, and electronic waste recycling. The framework that I developed is able to handle many decision-makers at the tiers of the networks, and enables the prediction of the flows of the materials between tiers as well as the prices at the tiers, along with the emissions generated, and the incurred costs and profits. I first developed a theoretical framework for supply chain networks with environmental concerns in the context of decision-making in the Information Age today. I allowed different decision-makers to weight the criteria (including the environmental ones) in distinct fashion. Subsequently, I generalized the original model to a global supply chain network model which included environmental criteria, electronic commerce, and risk management. I then developed an integrated reverse supply chain management framework that allows for the modeling, analysis, and computation of the material flows as well as the prices associated with the different tiers in the multitiered electronic recycling network. I also extended this model in order to deal with the environmental risk caused by hazardous material generated from the recycling processes. I assumed that the environmental risk due to hazardous material depends on the amount of residual hazardous material that is not extracted from electronic wastes by the processor as well as on the storage amount of hazardous waste that is not disposed yet by the hazardous material disposer. The models and computational methods were based on the methodologies of variational inequality theory for the study of the statics (cf. Nagurney (1999)) and projected dynamical systems for the dynamics (cf. Nagurney and Zhang (1996)).

This dissertation is concerned with a facility layout and traffic flow network design problem where the focus is on assigning activities to locations in order to minimize the congestion within a circulation system. This dissertation first presents a series of mathematical models of the facility layout problem in which stochastic congestion within the movement system is modelled. The models can be used to assist the design and placement of departments or activities within a facility or surrounding environment where the congestion of the pedestrian or customer traffic flow is of major concern. Numerical examples are provided to illustrate the difference between the various formulations. Second, a new heuristic algorithm called STEP, Sample Test pair-wise Exchange Procedure, to solve these complex problems is developed. With its straightforward approach, the algorithm can solve large-scale Quadratic and Stochastic Quadratic Assignment Problems with efficient computing times and excellent solution performance. Computational experience for solving many test examples is presented. Extensive work has been carried out for selecting and evaluating appropriate facility network design configurations. This is done by evaluating the performance of the alternative network designs such as star, grid, and ring topologies in terms of customers' sojourn time in the system. Finally, the dissertation concludes with a discussion of open problems and directions for future research.

Thesis (Ph. D.)--UCLA, 2004. / Vita. Description based on print version record. Includes bibliographical references (leaves 531-546).

Thesis (Ph. D.)--George Washington University, 2000. / Includes bibliographical references (leaves 199-208).