Reasoning with imprecise trade-offs in decision making under certainty and uncertainty

In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

The continuing evolution of official statistics: some challenges and opportunities

As economies, societies, and environments change, official statistics evolve and develop to reflect those changes. In reaction to disruptive innovations arising from globalisation, technological advances, and cultural changes, the pace of change of official statistics will accelerate in the future. The motivation for change may also be more existential than that of the past as official statisticians consider the survival of their discipline. This article examines some of the emerging developments and questions whether they present threats or offer opportunities.

Becoming a CEO: an exploration of the theory and practice of effective organisational leadership

This Thesis is an exploration of potential enhancement in effectiveness, personally, professionally and organisationally through the use of Theory as an Apparatus of Thought. Enhanced effectiveness was sought by the practitioner (Subject), while in transition to becoming Chief Executive of his organization. The introduction outlines the content and the structure of the University College Cork DBA. Essay One outlines what Theory is, what Adult Mental Development is and an exploration of Theories held in the Authors past professional practice. Immunity to change is also reflected on. Essay Two looks at the construct of the key Theories used in the Thesis. Prof. Robert Kegan’s Theory of Adult Mental Development was used to aid the generation of insight. The other key Theories used were The Theory of The Business, Theory of the Co‐operative and a Theory of Organisational Leadership. Essay Three explores the application of the key Theories in a professional setting. The findings of the Thesis were that the subject was capable of dealing with increased environmental complexity and uncertainty by using Theory as an Apparatus of Thought, which in turn enhanced personal, professional and organisational effectiveness. This was achieved by becoming more aware of the Theories held by the practitioner, the experiences from the application of those Theories, which then led to greater insight. The author also found that a detailed understanding of the Theory of the Business and a Theory of Leadership would support any new CEO in the challenging early part of their tenure.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.

The knowledge, attitudes and beliefs of patients and their healthcare professionals around oral dosage form modification: a systematic review of the qualitative literature

Objectives: The objective of this systematic review was to synthesize the available qualitative evidence on the knowledge, attitudes and beliefs of adult patients, healthcare professionals and carers about oral dosage form modification. Design: A systematic review and synthesis of qualitative studies was undertaken, utilising the thematic synthesis approach. Data sources: The following databases were searched from inception to September 2015: PubMed, Medline (EBSCO), EMBASE, CINAHL, PsycINFO, Web of Science, ProQuest Databases, Scopus, Turning Research Into Practice (TRIP), Cochrane Central Register of Controlled Trials (CENTRAL) and the Cochrane Database of Systematic Reviews (CDSR). Citation tracking and searching the references lists of included studies was also undertaken. Grey literature was searched using the OpenGrey database, internet searching and personal knowledge. An updated search was undertaken in June 2016. Review methods: Studies meeting the following criteria were eligible for inclusion; (i) used qualitative data collection and analysis methods; (ii) full-text was available in English; (iii) included adult patients who require oral dosage forms to be modified to meet their needs or; (iv) carers or healthcare professionals of patients who require oral dosage forms to be modified. Two reviewers independently appraised the quality of the included studies using the Critical Appraisal Skills Programme Checklist. A thematic synthesis was conducted and analytical themes were generated. Results: Of 5455 records screened, seven studies were eligible for inclusion; three involved healthcare professionals and the remaining four studies involved patients. Four analytical themes emerged from the thematic synthesis: (i) patient-centred individuality and variability; (ii) communication; (iii) knowledge and uncertainty and; (iv) complexity. The variability of individual patient’s requirements, poor communication practices and lack of knowledge about oral dosage form modification, when combined with the complex and multi-faceted healthcare environment complicate decision making regarding oral dosage form modification and administration. Conclusions: This systematic review has highlighted the key factors influencing the knowledge, attitudes and beliefs of patients and healthcare professionals about oral dosage form modifications. The findings suggest that in order to optimise oral medicine modification practices the needs of individual patients should be routinely and systematically assessed and decision-making should be supported by evidence based recommendations with multidisciplinary input. Further research is needed to optimise oral dosage form modification practices and the factors identified in this review should be considered in the development of future interventions.