Simulation-based multi-criteria decision making: an interactive method with a case study on infectious disease epidemics

Whenever a system needs to be operated by a central decision making authority in the presence of two or more conflicting goals, methods from multi-criteria decision making can help to resolve the trade-offs between these goals. In this work, we devise an interactive simulation-based methodology for planning and deciding in complex dynamic systems subject to multiple objectives and parameter uncertainty. The outline intermittently employs simulation models and global sensitivity analysis methods in order to facilitate the acquisition of system-related knowledge throughout the iterations. Moreover, the decision maker participates in the decision making process by interactively adjusting control variables and system parameters according to a guiding analysis question posed for each iteration. As a result, the overall decision making process is backed up by sensitivity analysis results providing increased confidence in terms of reliability of considered decision alternatives. Using the efficiency concept of Pareto optimality and the sensitivity analysis method of Sobol’ sensitivity indices, the methodology is then instantiated in a case study on planning and deciding in an infectious disease epidemic situation similar to the 2020 coronavirus pandemic. Results show that the presented simulation-based methodology is capable of successfully addressing issues such as system dynamics, parameter uncertainty, and multi-criteria decision making. Hence, it represents a viable tool for supporting decision makers in situations characterized by time dynamics, uncertainty, and multiple objectives

An object-oriented approach to structuring multicriteria decision support in natural resource management problems

Includes bibliographical references.The undertaking of MCDM (Multicriteria Decision Making) and the development of DSSs (Decision Support Systems) tend to be complex and inefficient, leading to low productivity in decision analysis and DSSs. Towards this end, this study has developed an approach based on object orientation for MCDM and DSS modelling, with the emphasis on natural resource management. The object-oriented approach provides a philosophy to model decision analysis and DSSs in a uniform way, as shown by the diagrams presented in this study. The solving of natural resource management decision problems, the MCDM decision making procedure and decision making activities are modelled in an object-oriented way. The macro decision analysis system, its DSS, the decision problem, the decision context, and the entities in the decision making procedure are represented as "objects". The object-oriented representation of decision analysis also constitutes the basis for the analysis ofDSSs

Spatial decision support system for the selection of an overhead electrical transmission line corridor.

This dissertation presents research into the possibility of using GIS Spatial Analysis and Multi-Criteria Decision Making to determine a corridor for electric overhead transmission power line routing. The research described in this dissertation examines the feasibility of developing a spatial decision support system to select an overhead transmission line corridor. This support system could also be used to perform scenario analysis. The selection model evaluates multiple environmental, ecological, electrical, aesthetic, engineering and socio-economic criteria spatially. Each criterion is weighted using a pair-wise comparison and is presented as a GIS layer. A suitability map is derived from the weighted layers using a weighted linear combination. A least cost path that represents the corridor most likely to contain the optimum route for an overhead electrical transmission line is derived from the suitability map

Regional Policy Evaluation : Ignorance, Evidence and Influence

The present UK government has adopted a “New Localism” in the operation of regional policy (Balls, 2002). This involves the delegation of discretionary powers to locally elected bodies, such as the Scottish Parliament and the Welsh Assembly, and a host of devolved agencies, such as the Regional Development Agencies (RDAs). We fear that because of standard asymmetric information problems, such policies will be extremely difficult to evaluate, which has implications for both their efficiency and democratic accountability. However, even without these particular extended principal agent problems, the effectiveness of regional policy is hard to measure. We illustrate this by discussing the issues raised in evaluating and appraising more conventional policies. In our approach we aim to be complementary with more practical surveys of regional policy evaluation (Taylor, 2002). We argue that evaluation raises issues of allocation, coordination, information and motivation. The optimal policy is difficult to identify, even with a very simple policy framework, because some of the outcomes are necessarily qualitative and others are conflicting. We hope that this discussion will be used to lay the ground for a more focussed future examination of the evaluation issues raised by the present and proposed regional policy framework

Fuzzy expert systems in civil engineering

Imperial Users onl

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

A technique for determining viable military logistics support alternatives

A look at today's US military will see them operating much beyond the scope of protecting and defending the United States. These operations now consist of, but are not limited to humanitarian aid, disaster relief, and conflict resolution. This broad spectrum of operational environments has necessitated a transformation of the individual military services into a hybrid force that can leverage the inherent and emerging capabilities from the strengths of those under the umbrella of the Department of Defense (DOD), this concept has been coined Joint Operations. Supporting Joint Operations requires a new approach to determining a viable military logistics support system. The logistics architecture for these operations has to accommodate scale, time, varied mission objectives, and imperfect information. Compounding the problem is the human in the loop (HITL) decision maker (DM) who is a necessary component for quickly assessing and planning logistics support activities. Past outcomes are not necessarily good indicators of future results, but they can provide a reasonable starting point for planning and prediction of specific needs for future requirements. Adequately forecasting the necessary logistical support structure and commodities needed for any resource intensive environment has progressed well beyond stable demand assumptions to one in which dynamic and nonlinear environments can be captured with some degree of fidelity and accuracy. While these advances are important, a holistic approach that allows exploration of the operational environment or design space does not exist to guide the military logistician in a methodical way to support military forecasting activities. To bridge this capability gap, a method called A Technique for Logistics Architecture Selection (ATLAS) has been developed. This thesis describes and applies the ATLAS method to a notional military scenario that involves the Navy concept of Seabasing and the Marine Corps concept of Distributed Operations applied to a platoon sized element. This work uses modeling and simulation to incorporate expert opinion and knowledge of military operations, dynamic reasoning methods, and certainty analysis to create a decisions support system (DSS) that can be used to provide the DM an enhanced view of the logistics environment and variables that impact specific measures of effectiveness.Ph.D.Committee Chair: Mavris, Dimitri; Committee Member: Fahringer, Philip; Committee Member: Nixon, Janel; Committee Member: Schrage, Daniel; Committee Member: Soban, Danielle; Committee Member: Vachtsevanos, Georg

An Intelligent Expert System for Decision Analysis and Support in Multi-Attribute Layout Optimization

Layout Decision Analysis and Design is a ubiquitous problem in a variety of work domains that is important from both strategic and operational perspectives. It is largely a complex, vague, difficult, and ill-structured problem that requires intelligent and sophisticated decision analysis and design support. Inadequate information availability, combinatorial complexity, subjective and uncertain preferences, and cognitive biases of decision makers often hamper the procurement of a superior layout configuration. Consequently, it is desirable to develop an intelligent decision support system for layout design that could deal with such challenging issues by providing efficient and effective means of generating, analyzing, enumerating, ranking, and manipulating superior alternative layouts. We present a research framework and a functional prototype for an interactive Intelligent System for Decision Support and Expert Analysis in Multi-Attribute Layout Optimization (IDEAL) based on soft computing tools. A fundamental issue in layout design is efficient production of superior alternatives through the incorporation of subjective and uncertain design preferences. Consequently, we have developed an efficient and Intelligent Layout Design Generator (ILG) using a generic two-dimensional bin-packing formulation that utilizes multiple preference weights furnished by a fuzzy Preference Inferencing Agent (PIA). The sub-cognitive, intuitive, multi-facet, and dynamic nature of design preferences indicates that an automated Preference Discovery Agent (PDA) could be an important component of such a system. A user-friendly, interactive, and effective User Interface is deemed critical for the success of the system. The effectiveness of the proposed solution paradigm and the implemented prototype is demonstrated through examples and cases. This research framework and prototype contribute to the field of layout decision analysis and design by enabling explicit representation of experts? knowledge, formal modeling of fuzzy user preferences, and swift generation and manipulation of superior layout alternatives. Such efforts are expected to afford efficient procurement of superior outcomes and to facilitate cognitive, ergonomic, and economic efficiency of layout designers as well as future research in related areas. Applications of this research are broad ranging including facilities layout design, VLSI circuit layout design, newspaper layout design, cutting and packing, adaptive user interfaces, dynamic memory allocation, multi-processor scheduling, metacomputing, etc

Treatment strategies in multiple sclerosis: Current and future practice considerations

This thesis focuses on clinically-relevant questions regarding the care of patients with relapsing remitting multiple sclerosis (RRMS), including appraisal of the current relevant literature regarding the disease itself and therapeutic approaches. An understanding of the nature of MS is detailed in a review of its characteristics and natural history in the pre-treatment era, to establish a baseline upon which the utility of disease modifying therapies (DMTs) in the modern era can be evaluated. A review of the history of therapeutics in MS leads into an appraisal of trials in the modern era, including potential and actual pitfalls in their design and interpretation. A comprehensive tabulation of the pivotal placebo-controlled and head-to-head DMT trials is included and allows an appreciation of the complexity in evaluating the evidence-base for the therapeutic options currently available. Inter-trial comparisons are often made despite differing patient populations, methods and outcome analyses and these are discussed. The potential for new therapeutic options is also considered in light of emerging evidence for novel treatment approaches. The original work in this thesis stems from practical clinical dilemmas in the management of patients with RRMS and uses real-world observational data to address them. The available evidence-base supports the early initiation of DMTs in RRMS on short-term efficacy grounds, but there remains controversy regarding the timing and aggressiveness of therapeutic intervention, particularly with higher risk treatments, and uncertainty regarding the impact on long-term outcomes. We have studied the safety and efficacy of the oral DMTs dimethyl fumarate and fingolimod in our own centre, and describe their safety and efficacy in real clinical practice. The availability of oral DMTs in MS therapeutics was a watershed event and our cohorts exemplify the desire of patients to switch from injectable therapies when alternatives became available. Whilst our data support the efficacy of these therapies, their side effects remain limiting for a proportion of patients, and this was higher than expected from previous trials. Additionally, we have been able to describe potential risk factors for lymphopaenia with dimethyl fumarate, and identify cases where this can persist despite drug discontinuation, which is relevant given its (post-licensing) association with progressive multifocal leukoencephalopathy (PML). In identifying RRMS patients with similar disease profiles within two centres in Scotland who were often treated differently, we have provided evidence of significant variation in practice in a close geographical area. Additionally, whilst outcome comparisons were hampered by methodological issues, there were significant reductions in some disease measures when DMTs were started sooner rather than later in statistically-matched cohorts. These cohorts now provide the opportunity for a prospective study to compare more detailed long-term outcomes in patients treated or not in the early stages of their disease. Lastly, a unique dataset is analysed to evaluate the safety and efficacy of switching from one powerful anti-inflammatory immune therapy to another, namely natalizumab to alemtuzumab, in highly active RRMS. This is an increasingly used strategy since the worldwide licensing of alemtuzumab, despite little evidence upon which to base the approach. The use of alemtuzumab in the UK and Ireland for many years before this licensing, as a result of its development in Cambridge, provided a multicentre cohort of patients with longitudinal follow-up unavailable elsewhere, and we have demonstrated that this sequencing appears safe and effective. Additionally, the management of the switch between these two treatments is a dilemma in itself and we present data to support a direct switch and avoiding prolonged delay beyond excluding the possibility of (subclinical) infections. The studies presented here are therefore of real utility to the practising clinician in MS therapeutics