This thesis describes the design optimization of two different types of vessels. They are LHA(R), a replacement for the US Navy amphibious assault ship and DDG51, a destroyer class vessel. The overall measure of effectiveness (OMOE) and the lead ship acquisition cost (LCA) are considered to be the objective functions. The evaluation of feasibility of the designs and various ship parameter calculations are performed using the US Navy ship design evaluation software ASSET. ASSET is integrated with the design optimization software DARWIN to obtain results representing the best designs over a range of LCA. Model Center software is used to integrate the processes ASSET and Darwin. The results generated will provide the owner with the best designs possible (designs with high OMOE) over a range of LCA. This thesis is mainly of academic interest. The results generated could help the owners to look at various design options available for the amount of money they are willing to spend. / Master of Science

The industrial gas industry represents a multi-billion dollar global market and provides essential product to manufacturing and service organizations that drive the global economy. In this dissertation, we focus on improving distribution efficiency in the industrial gas industry by addressing the strategic level problem of bulk tank allocation (BTA) while considering the effects of important operational issues. The BTA problem determines the preferred size of bulk tanks to assign to customer sites to minimize recurring gas distribution costs and initial tank installation costs. The BTA problem has a unique structure which includes a resource allocation problem and an underlying vehicle routing problem with split deliveries. In this dissertation, we provide an exact solution approach that solves the BTA problem to optimality and recommends tank allocations, provides a set of delivery routes, and determines delivery amounts to customers on each delivery route within reasonable computational time. The exact solution approach is based on a branch-and-price algorithm that solves problem instances with up to 40 customers in reasonable computational time. Due to the complexity of the problem and the size of industry representative problems, the solution approaches published in the literature rely on heuristics that require a set of potential routes as input. In this research, we investigate and compare three alternative route generation algorithms using data sets from an industry partner. When comparing the routes generation algorithms, a sweep-based heuristic was the preferred heuristic for the data sets evaluated. The existing BTA solution approaches in the literature also assume a single bulk tank can be allocated at each customer site. While this assumption is valid for some customers due to space limitations, other customer sites may have the capability to accommodate multiple tanks. We propose two alternative mathematical models to explore the possibility and potential benefits of allocating multiple tanks at designated customer site that have the capacity to accommodate more than one tank. In a case study with 20 customers, allowing multiple tank allocation yield 13% reduction in total costs. In practice, industrial gas customer demands frequently vary by time period. Thus, it is important to allocate tanks to effectively accommodate time varying demand. Therefore, we develop a bulk tank allocation model for time varying demand (BTATVD) which captures changing demands by period for each customer. Adding this time dimension increases complexity. Therefore, we present three decomposition-based solution approaches. In the first two approaches, the problem is decomposed and a restricted master problem is solved. For the third approach, a two phase periodically restricting heuristic approach is developed. We evaluate the solution approaches using data sets provided by an industrial partner and solve the problem instances with up to 200 customers. The results yield approximately 10% in total savings and 20% in distribution cost savings over a 7 year time horizon. The results of this research provide effective approaches to address a variety of distribution issues faced by the industrial gas industry. The case study results demonstrate the potential improvements for distribution efficiency. / Ph. D.

Many utility asset management programs have been developed following the U.S. Environmental Protection Agency (EPA) core definition of maintaining a level of service at the lowest life cycle cost. Most utilities, however, only incorporate performance measures into their asset management plans. A holistic approach to asset management is more beneficial because it takes into account the short and long term goals of the utility and can provide better service socially, economically, and environmentally. An analysis of the Town of Blacksburg wastewater utility's practices and data collection was performed using a holistic asset management framework developed at Virginia Tech. This theoretical framework supports the three key aspects of asset management: performance, sustainability, and resilience. Where gaps were identified, recommendations were made as to what practices, goals, and data the Town can add to their current plan so that their program is more holistic. Research has shown that many utilities have trouble adapting to asset management plans because job roles and responsibilities change and are often not well defined. To help the Town of Blacksburg adapt to their new asset management plan with performance, sustainability and resiliency goals, a work process flow was designed. A work process flow allows for visible changes in job responsibility to be more easily recognized as well as allow for future changes to be made. / Master of Science

The limited available budget along with old aging infrastructure in nation magnifies the role of strategic decision making for maintenance of infrastructure. The challenging objective is to maintain the infrastructure asset systems in a state of good repair and to improve the efficiency and performance of the infrastructure systems while protecting and enhancing the natural environment. Decision makers are in need of a decision support system to consider these multiple objectives and criteria to effectively allocate funding and achieve the highest possible return on investment on their infrastructure. The research proposes and validates a framework for such decisions. The proposed model aims at finding optimal techniques for maintenance of multiple roadway asset items while taking into account time, cost, level of service and environmental impacts. Therefore, the goal is to answer what are the optimal combinations of maintenance techniques for roadway assets while more than one objective is being optimized. In other words, the main objective is to develop a decision support system for selecting and prioritizing necessary actions for MRandR (Maintenance, Repair and Rehabilitation) of multiple asset items in order for a roadway to function within an acceptable level of service, budget, and time while considering environmental impacts. To achieve these desirable outcomes, this model creates a two-stage framework for a sustainable infrastructure asset management. First a multi-objective problem based on the multi colony ant colony optimization is analyzed. The objectives of the problem are: (i) Minimizing maintenance costs, (ii) Minimizing maintenance time, (iii) Minimizing environmental impacts and (iv) Maximizing level of service improvement. In the second stage, the results of the multi objective optimization will be prioritized using a Multi Criteria Decision Making (MCDM) process. The proposed approach will simultaneously optimize four conflicting objectives along with using a multi criteria decision-making technique for ranking the resulted non-dominated solutions of multi objective optimization. The results of implementation of the proposed model on a section of I-64 highway are presented for a sub-set of asset items. Moreover, the proposed model is validated using a scalable test problem as well as comparison with existing examples. Results reveal the capability of the model in generation of optimal solutions for the selection of maintenance strategies. The model optimizes decision making process and benefits decision makers by providing them with solutions for infrastructure asset management while meeting national goals towards sustainability and performance-based approach. In addition, provides a tool to run sensitivity analysis to evaluate annual budget effects and environmental impacts of different resource allocation scenarios. Application of the proposed approach is implemented on roadway asset items but it is not limited to roadways and is applicable to other infrastructure assets. / Ph. D.

Yes / A portfolio optimisation problem involves allocation of investment to a number of different assets to maximize return and minimize risk in a given investment period. The selected assets in a portfolio not only collectively contribute to its return but also interactively define its risk as usually measured by a portfolio variance. This presents a combinatorial optimisation problem that involves selection of both a number of assets as well as its quantity (weight or proportion or units). The problem is extremely complex due to a large number of selectable assets. Furthermore, the problem is dynamic and stochastic in nature with a number of constraints presenting a complex model which is difficult to solve for exact solution. In the last decade research publications have reported the applications of metaheuristic-based optimisation methods with some success., This paper presents a review of these reported models, optimisation problem formulations and metaheuristic approaches for portfolio optimisation.

The objective of the thesis is to find out whether expansionary monetary policy creates an upward pressure on asset prices and can thus create asset price bubbles, or more precisely significantly contribute to their creation. In doing so, we test the significance and the sign of coefficient on monetary policy stance indicator as a determinant of real estate and stock prices on 19 OECD countries quarterly panel data since 1980. Further we assess periods of real estate and stock price bubbles and periods of expansionary monetary policy and examine their relationship. The asset price bubbles are assessed on the basis of relevant price indices developments without examining the underlying fundamentals. Based on our results it appears that expansionary monetary policy has a positive effect on real estate prices and can thus contribute to formation of real estate bubbles. The effect on stock prices is ambiguous and mostly statistically insignificant. By examining the relationship between assessed asset price bubbles and periods of expansionary monetary policy we found out that monetary expansion is neither sufficient nor necessary condition for formation of asset price bubbles but also that there is a relatively strong relationship between these events. JEL Classification C23, E43, E52, E58, G12, N10, N20...

by Chan Chi Kan. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1987. / Bibliography: leaves 57-59.

Zhang Xixi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 90-91). / Abstracts in English and Chinese. / Chapter I. --- Introduction --- p.6 / Chapter II. --- Literature Review --- p.10 / Chapter III. --- Hypotheses and Design of the Tests --- p.22 / Chapter IV. --- Data and Findings --- p.34 / Chapter A. --- Data Source --- p.34 / Chapter B. --- Selection of Sample BHCs --- p.35 / Chapter C. --- BHC Size and Description Securitization --- p.38 / Chapter 1). --- Description of BHC Size --- p.38 / Chapter 2). --- Types of Securitization --- p.43 / Chapter V. --- Results --- p.46 / Chapter A. --- Differences Between Securitizing and Non-securitizing BHC Characteristics --- p.46 / Chapter 1). --- Univariate Test between Securitizing and Non-securitizing banks Characteristics --- p.47 / Chapter 2). --- Joint Test of Difference between Mean Values of the Characteristics --- p.61 / Chapter B. --- Correlations among Variables --- p.62 / Chapter 1). --- Correlation within Same Characteristics Class --- p.63 / Chapter 2). --- Correlation among Different Characteristics --- p.65 / Chapter C. --- To Explain Decision on Securitization --- p.67 / Chapter D. --- Linear Regression to Explain the Degree of Securitizing Among Securitizing Banks --- p.75 / Chapter V. --- Conclusion and Insights for Future Research --- p.82 / Chapter A. --- Conclusion --- p.82 / Chapter B. --- Future Research --- p.87 / Chapter VI. --- References --- p.90 / Chapter VII. --- Appendix --- p.92

O setor aeroportuário apresentou forte crescimento nos últimos anos, ressaltando as ineficiências na gestão de sua infraestrutura e de seus ativos, especialmente no Brasil. Assim, com a exaustão das técnicas tradicionais para a redução de custos, as empresas necessitam buscar melhorias apoiadas no uso de métodos mais complexos a fim de aumentar a produtividade de seus ativos. Desta forma, desponta a necessidade de modelos para a identificação da vida útil e análise da substituição econômica de ativos, uma vez que estas informações auxiliam na tomada de decisão e conduzem a melhores planos de manutenção, reduzindo as perdas do processo. Assim sendo, este trabalho tem por objetivo propor e aplicar uma sistemática para avaliação da substituição de ativos no setor aeroportuário, apoiado em modelos adequados às especificidades do setor através do estudo das suas variáveis. Para isto, são identificados os elementos que influenciam na vida útil dos ativos e, posteriormente, modelos de identificação de vida útil e substituição econômica de ativos são propostos e aplicados em um aeroporto brasileiro de grande porte. Pode-se concluir que a sistemática produziu resultados consistentes e que auxiliam a decisão de substituição de ativos de uma forma estruturada. / In the past years, an increase in aviation transport can be noticed and it highlights inefficiencies in asset management, especially in Brazil. Hence, the exhaustion of traditional techniques to cost reduction lead companies to seek improvements supported by more complex methods in order to increase productivity of their assets. Thus, it is crucial to develop models for useful life identification and economic replacement of assets, since these information assist the decision making process and lead to better maintenance plans, reducing wastage. As a result, the main objective of this work is develop and apply a systematic for evaluation of asset replacement in airports, supported by models that consider the specificities of the aviation sector and its particular variables. In this direction, elements that influence assets useful life are identified and, then, models for useful life identification and economic replacement of assets are developed and applied in an important Brazilian airport. It can be concluded that the systematic have produced consistent results and can assist in asset replacement decision in a structured form.

Liquidity (LQ) and asset quality (AQ) management present significant challenges to mortgage bankers in their efforts to improve profitability (PR). When liquidity increases, there is no positive impact on mortgage asset growth; however, this trend indicates that asset management and liquidity positions are not well managed. To run a viable mortgage business, mortgage bankers need to have a good grasp of the association between LQ, AQ, and PR. Anchored in the profit theory paradigm, the purpose of this multiple regression study was to examine the relationship between LQ, AQ, and PR of mortgage banks (MBs) in Nigeria. Archival financial data of 16 randomly sampled MBs covering a period of 8 years from 2009 to 2016 were used. Data were analyzed using multiple panel regression incorporating two PR models, net interest margin (NIM) and return on asset (ROA). The regression result indicated that LQ and AQ constructs significantly predicted PR as measured by NIM because F (8, 80) = 2.061, p = 0.014, p < 0.05, and effect size given by R2 = 0.458, signifying 46% variation in NIM. The model of PR as measured by ROA also indicated that LQ and AQ constructs were significant because F (8, 80) = 4.043, p = 0.000, p < 0.05, with effect size measured by R2 = 0.624, indicating 62% variation in ROA. The findings emphasized the need for optimization of LQ and AQ to maximize PR. The implications for positive social change include the potential to provide the business leaders in the mortgage industry with knowledge about optimization of LQ and AQ as drivers of PR. In addition, when business owners achieve increase profitability, they may provide more employment opportunities, better working conditions, better compensation plans, and more access to mortgage finance options.