Multicriteria analysis under uncertainty with IANUS - method and empirical results

IANUS is a method for aiding public decision-making that supports efforts towards sustainable development and has a wide range of application. IANUS stands for Integrated Assessment of Decisions uNder Uncertainty for Sustainable Development. This paper introduces the main features of IANUS and illustrates the method using the results of a case study in the Torgau region (eastern Germany). IANUS structures the decision process into four steps: scenario derivation, criteria selection, modeling, evaluation. Its overall aim is to extract the information needed for a sound, responsible decision in a clear, transparent manner. The method is designed for use in conflict situations where environmental and socioeconomic effects need to be considered and so an interdisciplinary approach is required. Special emphasis is placed on a broad perception and consideration of uncertainty. Three types of uncertainty are explicitly taken into account by IANUS: development uncertainty (uncertainty about the social, economic and other developments that affect the consequences of decision), model uncertainty (uncertainty associated with the prediction of the effects of decisions), and weight uncertainty (uncertainty about the appropriate weighting of the criteria). The backbone of IANUS is a multicriteria method with the ability to process uncertain information. In the case study the multicriteria method PROMETHEE is used. Since PROMETHEE in its basic versions is not able to process uncertain information an extension of this method is developed here and described in detail. --

Preference Modelling

This paper provides the reader with a presentation of preference modelling fundamental notions as well as some recent results in this field. Preference modelling is an inevitable step in a variety of fields: economy, sociology, psychology, mathematical programming, even medicine, archaeology, and obviously decision analysis. Our notation and some basic definitions, such as those of binary relation, properties and ordered sets, are presented at the beginning of the paper. We start by discussing different reasons for constructing a model or preference. We then go through a number of issues that influence the construction of preference models. Different formalisations besides classical logic such as fuzzy sets and non-classical logics become necessary. We then present different types of preference structures reflecting the behavior of a decision-maker: classical, extended and valued ones. It is relevant to have a numerical representation of preferences: functional representations, value functions. The concepts of thresholds and minimal representation are also introduced in this section. In section 7, we briefly explore the concept of deontic logic (logic of preference) and other formalisms associated with "compact representation of preferences" introduced for special purpoes. We end the paper with some concluding remarks

Political strategies of external support for democratization

Political strategies of external support to democratization are contrasted and critically examined in respect of the United States and European Union. The analysis begins by defining its terms of reference and addresses the question of what it means to have a strategy. The account briefly notes the goals lying behind democratization support and their relationship with the wider foreign policy process, before considering what a successful strategy would look like and how that relates to the selection of candidates. The literature's attempts to identify strategy and its recommendations for better strategies are compared and assessed. Overall, the article argues that the question of political strategies of external support for democratization raises several distinct but related issues including the who?, what?, why?, and how? On one level, strategic choices can be expected to echo the comparative advantage of the "supporter." On a different level, the strategies cannot be divorced from the larger foreign policy framework. While it is correct to say that any sound strategy for support should be grounded in a theoretical understanding of democratization, the literature on strategies reveals something even more fundamental: divergent views about the nature of politics itself. The recommendations there certainly pinpoint weaknesses in the actual strategies of the United States and Europe but they have their own limitations too. In particular, in a world of increasing multi-level governance strategies for supporting democratization should go beyond preoccupation with just an "outside-in" approach

Decision aiding in off-grid electrification projects: the role of uncertainty acknowledgement and objectives alignment

Most completed South African off-grid electrification projects have failed to contribute significantly to the sustainable development of the communities they supply. The hypothesis of this research is that the root causes of these failures can often be found in the pre-implementation decision making (planning) processes, specifically in three areas: 1. Decision aiding approaches and tools, aimed at supporting the decision making process, are either not used or do not support high quality decisions. 2. Uncertainties that can impact the project negatively are often not acknowledged (identified) initially, and can therefore not be addressed proactively. 3. The primary project objectives often do not align with sustainable development objectives, which mean that even if all the project objectives are achieved (i.e. a successful project) the project still does not contribute to sustainable development. The process of validating this hypothesis results in several outputs aimed at improving the contribution of future off-grid electrification projects to sustainable development: A framework of primary energisation objectives for sustainable development is developed, which defines what the outcomes of a successful off-grid electrification project should be. High quality decision making is defined, and a framework of decision aiding characteristics that support high quality decision making is developed against which decision aiding approaches and tools can be evaluated. The concept of soft and hard uncertainties is introduced, and it is shown that most of the social and institutional unacknowledged uncertainties in South African off-grid projects are hard. Hard uncertainties are impossible to represent probabilistically, and are difficult to include in traditional single-dimensional (mostly cost-based) decision aiding approaches and tools. A degree of surprise tool, based on Shackle's measure of a decision maker's degree of surprise at a future outcome becoming reality, is developed to act as an example of how hard uncertainty can be acknowledged in the decision making process. p14 - Abstract Soft uncertainty in the decision process is quantified for two examples: renewable energy system sizing, where an adequacy confidence index is proposed, and renewable energy resource estimation, where the accuracy and applicability of RETScreen and Homer within a South African climatic context are analysed. Finally, the above outputs are integrated into an existing decision aiding process and applied in order to demonstrate the value of decision aiding which includes uncertainty acknowledgement and objectives alignment. The applicability of the results of this research is not limited to off-grid electrification, and can be of value within any developmental project aligned with sustainable development, especially where social and institutional uncertainties are prevalent

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country