Planning for the strategic management of South Africa's West Coast rock lobster fishery : an integrated approach to group decision support

Bibliography: leaves 175-184.As Bryson (1995) points out, strategic planning is particularly useful for assisting organisations and communities to deal with change. This study was carried out at a time of great change in South Africa, when a new fisheries policy was being formulated and negotiated. The research describes an intervention with a group of .fisheries managers, scientists, fishing company directors and other key stakeholders, in planning for the future management of the West Coast Rock Lobster fishery. The primary objective of the study was to consider an integrated approach to group decision support, incorporating a particular soft-OR approach, SODA, together with multi-criteria decision analysis (MCDA). An integration of these two approaches has recently been suggested by researchers, for several reasons. Firstly, different phases of an intervention usually involve different tasks. Secondly, mixing methodologies will enable different aspects of the problem to be modelled and analysed. SODA was used at the outset, for divergent exploration and structuring of the problems surrounding the development of an operational management procedure (OMP) for the fishery, including more subjective and qualitative information. Several stakeholder groups opposed the idea of an OMP in the form in which it was proposed

Conflicting Objectives in Decisions

This book deals with quantitative approaches in making decisions when conflicting objectives are present. This problem is central to many applications of decision analysis, policy analysis, operational research, etc. in a wide range of fields, for example, business, economics, engineering, psychology, and planning. The book surveys different approaches to the same problem area and each approach is discussed in considerable detail so that the coverage of the book is both broad and deep. The problem of conflicting objectives is of paramount importance, both in planned and market economies, and this book represents a cross-cultural mixture of approaches from many countries to the same class of problem

Uncertainty management for coastal defence systems.

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN029923 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Decision support systems for solving discrete multicriteria decision making problems

Includes bibliography.The aim of this study was the design and implementation of an interactive decision support system, assisting a single decision maker in reaching a satisfactory decision when faced by a multicriteria decision making problem. There are clearly two components involved in designing such a system, namely the concept of decision support systems (DSS) and the area of multicriteria decision making (MCDM). The multicriteria decision making environment as well as the definitions of the multicriteria decision making concepts used, are discussed in chapter 1. Chapter 2 gives a brief historical review on MCDM, highlighting the origins of some of the more well-known methods for solving MCDM problems. A detailed discussion of interactive decision making is also given. Chapter 3 is concerned with the DSS concept, including a historical review thereof, a framework for the design of a DSS, various development approaches as well as the components constituting a decision support system. In chapter 4, the possibility of integrating the two concepts, MCDM and DSS, are discussed. A detailed discussion of various methodologies for solving MCDM problems is given in chapter 5. Specific attention is given to identifying the methodologies to be implemented in the DSS. Chapter 6 can be seen as a theoretical description of the system developed, while Chapter 7 is concerned with the evaluation procedures used for testing the system. A final summary and concluding remarks are given in Chapter 8

Multi-objective Optimization of Reservoir Operation Under Uncertainty with Robust and Flexible Decision Variables

Optimization of reservoir operation is involves various competing objectives for a scarce resource (water). To find the optimal operation of reservoirs, it is essential to consider multiple objectives simultaneously. There are various sources of uncertainty associated with the reservoir operation problem that should be considered as well. The overarching goal of this research is to develop a framework for finding flexible and reliable solutions to the reservoir operation problem with competing objectives. Because some sources of uncertainty are not well quantified, providing flexible decision variables lets the decision maker choose accordingly from a range of options knowing that all the flexible decision variables are feasible with a specified probability of failure and that are relatively optimal. To accomplish this goal, each flexible decision variable is represented by a random variable within a specific range instead of a single deterministic decision variable. An additional objective is added to the optimization problem, in order to maximize the flexibility of decision variables. The proposed methodology is tested for two mathematical test problems and the operation of the Grand Coulee reservoir, which is located on the Columbia River in the Northwestern United States. The Stochastic Collocation (SC) method is used to sample the random variables and approximate the expected values of the objectives. For the Grand Coulee reservoir, the decision variables are the daily turbine outflows. The first objective of the optimization is to minimize the forebay elevation deviation at the end of the optimization period. The second objective is to maximize the revenue from the hydropower production. The results show that the proposed methodology could find some flexible decision variables with 45% coefficient of variation. The corresponding expected objectives have less than 20% deterioration from the deterministic Pareto solutions. However, the number of function evaluations increases exponentially with the number of decision variables. Therefore, this methodology is suggested for problems with a few decision variables. For finding flexible decision variables in problems with many decision variables, a dimension reduction method called Karhunen Loeve (KL) expansion is implemented in the optimization problem. By extracting useful information from the decision variables, the decision space can be represented with merely a few random variables using a set of deterministic decision variables. The results show that three random variables are sufficient to generate decision variable realizations which have mean and variance less than 1% and 5% different from the original decision variable realizations, respectively. The proposed methodology is capable of efficiently finding flexible decision variables that lead to expected objective values close to the Pareto deterministic solutions. To force the generated decision variable realizations to stay within the feasible bounds and therefore reduce the number of constraints that need to be checked, the data is transformed to be within bounds first, and then the KL-expansion is performed. Using the transformed data decreases the computational time but the decrease in computational time is not significant. The inflow uncertainty is also considered as the only source of input uncertainty. Forecast inflow ensembles can be used as the source of inflow uncertainty. However in this study due to lack of information, historical inflows are used instead. The inflow uncertainties are represented using the KL-expansion. Robust optimization is performed by optimizing the weighted sum of the expectation and standard deviation of the objective due to uncertain inflows. The weights in the robust objective formulation can be changed based on the decision maker’s preference of robustness versus performance. Finally, the combined framework to find robust and flexible decision variables is tested on a reservoir operation problem and the results were compared to the deterministic case

A Decision Analysis Perspective on Multiple Response Robust Optimization

Decisions in which multiple objectives must be optimized simultaneously occur frequently in government, military, and industrial settings. One method a decision maker may use to assist in such decisions is the application of a desirability function. An informed specification of the desirability function\u27s parameters is essential to accurately describe the decision maker\u27s value trade-offs and risk preference. This thesis uses utility transversality to analyze the implicit trade-off and risk attitude assumptions attendant to the desirability function. The desirability function does not explicitly account for response variability. A robust solution takes not only the expected response into account, but also its variance. Assessing a utility function over desirability as a means to describe the decision maker\u27s risk attitude produces a robust operating solution consistent with those preferences. This thesis examines robustness as it applies to the desirability function in a manufacturing experiment example. Different levels of diplomatic, informational, military, and economic (DIME) instruments of national policy are investigated to examine their effect on the political, military, economic, social, infrastructure, and information (PMESII) systems of a nation. AFRL\u27s National Operational Environment Model (NOEM) serves as a basis for identifying a robust national policy in a scenario involving the Democratic Republic of Congo

A Quantitative Decision Support Model to Aid Selection of Combat Aircraft Force Mixes for Contingency Deployment

Selection of combat aircraft during crisis action planning can be of critical importance. In determining the value of force mixes, it is proposed that one can evaluate extrinsic and intrinsic value separately. Intrinsic value is the designed capability of a weapons platform to accomplish a specified aerospace mission. Extrinsic value is the expected appropriateness of such platforms, given the environmental characteristics in which they must operate. This research develops a decision support tool for planners in determining the extrinsic value of force mixes, which then expedites the selection of best overall force mixes. The research included: content analysis of official guidance, Critical Decision Methodology interviews, a Delphi study (to define and quantify the factors, and establish a hierarchy and global weights), generation of the Value Focused Thinking decision tool, and establishment of an appropriate relationship between extrinsic and intrinsic value. This research provides planners-throughout the USAF-with a decision support tool that objectively compares alternative force packages for specific deployments. This represents a first step toward codifying or formalizing the art of force selection. These results will help reduce the crisis action response timeline, and should lead to more accurate modeling of force mix applicability

Interactive Decision Analysis; Proceedings of an International Workshop on Interactive Decision Analysis and Interpretative Computer Intelligence, Laxenburg, Austria, September 20-23, 1983

An International Workshop on Interactive Decision Analysis and Interpretative Computer Intelligence was held at IIASA in September 1983. The Workshop was motivated, firstly, by the realization that the rapid development of computers, especially microcomputers, will greatly increase the scope and capabilities of computerized decision-support systems. It is important to explore the potential of these systems for use in handling the complex technological, environmental, economic and social problems that face the world today. Research in decision-support systems also has another, less tangible but possibly more important, motivation. The development of efficient systems for decision support requires a thorough understanding of the differences between the decision-making processes in different nations and cultures. An understanding of the different rationales underlying decision making is not only necessary for the development of efficient decision-support systems, but it is also an important factor in encouraging international understanding and cooperation. The Proceedings of the Workshop which are contained in this volume are divided in four main sections. The first section consists of an introductory lecture in which a unifying approach to the use of computers and computerized mathematical models for decision analysis and support is described. The second section is concerned with approaches and concepts in interactive decision analysis and section three is devoted to methods and techniques for decision analysis. The final section contains descriptions of a wide range of applications of interactive techniques, covering the fields of economics, public policy planning, energy policy evaluation, hydrology and industrial development