Existing approaches to continuous optimization are essentially mechanisms for deciding which locations should be sampled in order to obtain information about a target function's global optimum. These methods, while often effective in particular domains, generally base their decisions on heuristics developed in consideration of ill-defined desiderata rather than on explicitly defined goals or models of the available information that may be used to achieve them. The problem of numerical optimization is essentially one of deciding what information to gather, then using that information to infer the location of the global optimum. That being the case, it makes sense to model the problem using the language of decision theory and Bayesian inference. The contribution of this work is precisely such a model of the optimization problem, a model that explicitly describes information relationships, admits clear expression of the target function class as dictated by No Free Lunch, and makes rational and mathematically principled use of utility and cost. The result is an algorithm that displays surprisingly sophisticated behavior when supplied with simple and straightforward declarations of the function class and the utilities and costs of sampling. In short, this work intimates that continuous optimization is equivalent to statistical inference and decision theory, and the result of viewing the problem in this way has concrete theoretical and practical benefits.

This research spans a variety of research topics with a common theme, providing decision support through the development and analysis of methods that assist decision making for natural resource and wildlife management. I used components of structured decision making and decision analysis to address natural resources management problems, specifically monitoring and estimating the status of harvested populations, as well as data collection decisions for landscape conservation. My results have implications for the way populations are monitored and their status is estimated. I find that the inclusion of error in data collection can have a substantial impact of the performance of abundance and growth rate estimates of harvested species and that the selection of estimation methods depends on what management objectives are most important. For example, the Sex-Age-Kill population estimation method best estimates the size of populations, while the Downing population reconstruction method better estimates trends in population growth rates. I provide a framework to support selection of the best estimation method while considering a monitoring program as a whole. Based on this framework the Vermont Fish and Wildlife Department will obtain the most benefits from a monitoring program including necropsy analysis that uses the Downing method to track population status. Finally, I demonstrated the use of value of information analysis as a tool to determine the relative expected benefits of addition spatial data collection for use in landscape mapping and conservation. This type of analysis can provide conservation agencies with a planning tool to direct budgets and mapping efforts.

The long-term success of wildlife conservation depends on maximizing the benefits of limited funds and data in pursuit of population and habitat objectives. The ultimate currency for wildlife management is progress toward long-term preservation of ample, wild, free wildlife populations and to this end, funds must be wisely spent and maximal use made from limited data. Through simulation-based analyses, I evaluated the efficacy of various models for estimating population abundance from harvest data. Because managers have different estimators to choose from and can also elect to collect additional data, I compared the statistical performance of different estimation strategies (estimator + dataset) relative to the financial cost of data collection. I also performed a value of information analysis to measure the impact that different strategies have on a representative harvest management decision. The latter analysis is not based on the cost of data, but rather on the management benefit derived from basing decisions on different datasets. Finally, I developed a hybrid modeling framework for mapping habitat quality or suitability. This framework makes efficient use of expert opinion and empirical validation data in a single, updatable statistical structure. I illustrate this method by applying it across an entire state.

The thesis is dealing with the methods of management of an enterprise and its information system. The main goal of this thesis is to depict the ties of those methods. The other goals are derived from the main one. They are structuring management methods and evaluating the appropriateness for managing IT in the small and medium enterprise. The first step for thorough mapping of the ties is structuring the methods into clearly defined approaches. The criteria gained from the systematic approach to enterprise are used for the analysis of the management methods. The mainly used management methods which have the impact on operational activity and distinct innovative character enter the analysis. In the next chapter, the basic ties of the approaches to the department of business informatics, information system and to the methods of business informatics are set. Subsequently the outputs relevant to business informatics management are extracted. The main contribution of the thesis lies in the systematic approach to methods of management which enables further research of ties to information system and its management. The second more concrete contribution lies in basic definition of the conclusions for the needs of business informatics.

Returned products of many industries are transported backwards through supply chains for recovery, thus forming &ldquo / closed-loop supply chains&rdquo / . Benefits, forthcoming with more effective management of recovery of returns are gaining importance. However, some issues, such as lack of information required to assess the quality of the returned products, may translate into critical uncertainties in the product recovery decisions and prevent closed-loop supply chains from operating efficiently. Hence, it is envisaged that significant economies may be attained by increasing the quantity of information fed into the planning decisions related to returned products. Thus, the objective of this study is to test the hypothesis that ready availability of perfect quality grade information associated with returned products by means of &ldquo / embedded systems&rdquo / , may lead to improved over all performance of recovery operations. To this end, in this thesis, linear programming models of generic multistage recovery processes are built. It is demonstrated by computational studies that significant gains may be obtained especially in environments where the prices of recovered products are decreasing in time.

Advancements in information technology enabled to track real time data in a more accurate and precise way in many manufacturing facilities. However, before obtaining the more accurate and precise data, the investment in information technology should be validated. Value of information may be adopted as a criterion in this investment. In this study, we analyze the value of information in a manufacturing facility where production and lead time quotation decisions are taken. In order to assess the value of information, two settings are analyzed. Under the first setting, the manufacturer takes decisions under perfect information. To find the optimal decisions under perfect information, a stochastic model is introduced. Under the second setting, the manufacturer takes decisions under imperfect information. To obtain a solution for this problem, Partially Observable Markov Decision Process is employed. Under the second setting, we study two approaches. In the first approach, we introduce a nonlinear programming model to find the optimal decisions. In the second approach, a heuristic approach, constructed on optimal actions taken under perfect information is presented. We examine the value of information under different parameters by considering the policies under nonlinear programming model and heuristic approach. The profit gap between the two policies is investigated. The effect of Make-to-Order (MTO) and Make-to-Stock (MTS) schemes on the value of information is analyzed. Lastly, different lead time quotation schemes / accept-all, accept-reject and precise lead time / are compared to find under which quotation scheme value of information is highest.

Designers are challenged to manage customer, technology, and socio-economic uncertainty causing dynamic, unquenchable demands on limited resources. In this context, increased concept flexibility, referring to a designer s ability to generate concepts, is crucial. Concept flexibility can be significantly increased through the integrated design of product and material concepts. Hence, the challenge is to leverage knowledge of material structure-property relations that significantly affect system concepts for function-based, systematic design of product and materials concepts in an integrated fashion. However, having selected an integrated product and material system concept, managing complexity in embodiment design-processes is important. Facing a complex network of decisions and evolving analysis models a designer needs the flexibility to systematically generate and evaluate embodiment design-process alternatives. In order to address these challenges and respond to the primary research question of how to increase a designer s concept and design-process flexibility to enhance product creation in the conceptual and early embodiment design phases, the primary hypothesis in this dissertation is embodied as a systematic approach for integrated product, materials and design-process design. The systematic approach consists of two components i) a function-based, systematic approach to the integrated design of product and material concepts from a systems perspective, and ii) a systematic strategy to design-process generation and selection based on a decision-centric perspective and a value-of-information-based Process Performance Indicator. The systematic approach is validated using the validation-square approach that consists of theoretical and empirical validation. Empirical validation of the framework is carried out using various examples including: i) design of a reactive material containment system, and ii) design of an optoelectronic communication system.

This thesis presents a methodology to incorporate reservoir uncertainties and estimate the loss in project value when facility planning decisions are based on erroneous estimates of input variables. We propose a tank model along with integrated asset development model to simulate the concept selection process. The model endogenizes drilling decisions and includes an option to expand. Key decision variables included in the model are number of pre-drill wells, initial facility capacity and number of well slots. Comparison is made between project value derived under erroneous estimates for reserve size and under an alternate hypothesis. The results suggest loss in project value of up to 40% when reservoir estimates are erroneous. Moreover, both optimistic and pessimistic reserve estimates results in a loss in project value. However, loss in project value is bigger when reserve size is underestimated than when it is overestimated. / text

Abstract Based on the sequential auction model of Kyle (1985) and embedded the formulation of positive feedback traders in De Long et al. (1990), our model formulates a recursive market game of insiders, noise traders, and market makers. In particular, the submitted demands of positive feedback inertial traders are influenced by previous own trading quantities. I prove the existence and uniqueness of a recursive linear equilibrium with positive feedback inertial trades. Further, the equilibrium calibrates that the strategies of insider and market makers are also influenced by positive feedback trades. Finally, we conduct a simulation analysis to get a price-volume pattern with some empirical interesting implications. Finally, this thesis takes trading strategies to trade the individual stock in TSEC. Although the market mechanism of TSEC has no market makers, it is still expected that these trading strategies are useful for traders which implies the information is filtrated by these trading strategies.

Clinical laboratory test results are integral to patient management. Important aspects of laboratory tests’ contributions are the use of the test information and the role they have in facilitating efficient and effective use of healthcare resources. Methods of measuring those contributions were examined using quantitative HCV RNA test results (HCV VL) in therapeutic management decisions as a model. Test precision is important in those decisions; therefore, the clinical use was evaluated by studying the impact that knowledge of inherent assay imprecision had on clinicians’ decisions. A survey describing a simulated patient at a decision point for HCV triple-combination therapy management was sent to 1491 hepatology clinicians. Participants saw HCV RNA results at five different levels and were asked to choose to: continue therapy, discontinue therapy, or repeat the test. Test results were presented both with and without the 95% confidence intervals (CIs). Three of the VLs had CIs that overlapped the therapeutic decision level. Participants saw both sets of results in random order. Demographics and practice preferences were also surveyed. One-hundred-thirty-eight responses were received. Adherence to clinical guidelines was demonstrated in self-reported behaviors and in most decisions. However, participants chose to repeat the test up to 37% of the time. The impact of the knowledge of assay imprecision did not have a statistically significant effect on clinicians’ decisions. To determine economic value, an analytic decision-tree model was developed. Transition probabilities, costs, and Quality of Life values were derived from published literature. Survey respondents’ decisions were used as model inputs. Across all HCV VL levels, the calculated test value was approximately $2600, with up to $17,000 in treatment-related cost savings per patient at higher HCV VLs. The test value prevailed regardless of the presence or absence of CIs, and despite repeat testing. The calculated value in cost savings/patient was up to 100 times the investment for HCV VL testing. Laboratory tests are investments in efficient uses of healthcare resources. Proper interpretation and use of their information is integral to that value. This type of analysis can inform institutional decisions and higher level policy discussions.