Evaluation of Environmental Policy Strategies with Imprecise Preference Information

Multicriteria decision making techniques give a decision maker a way to thoroughly analyze complex problems and state his or her arguments for decisions. The techniques usually require precise numerical information of the decision maker's preferences and the parameters of a decision problem. However, it is most often difficult to get this information. There may be several decision makers which have different opinions and the parameters of the decision problem may be ambiguous. Preference Assessment by Imprecise Ratio Statements (PAIRS) is a hierarchical weighting technique which allows decision makers to give preference statements with intervals instead of single point estimates. Here this new technique is applied to two case studies where decision makers have to select the most suitable solution from a discrete set of alternatives for a problem which involves several conflicting environmental and economic factors

Using interval weights in MADM problems

The choice of weights vectors in multiple attribute decision making (MADM) problems has generated an important literature, and a large number of methods have been proposed for this task. In some situations the decision maker (DM) may not be willing or able to provide exact values of the weights, but this difficulty can be avoided by allowing the DM to give some variability in the weights. In this paper we propose a model where the weights are not fixed, but can take any value from certain intervals, so the score of each alternative is the maximum value that the weighted mean can reach when the weights belong to those intervals. We provide a closed-form expression for the scores achieved by the alternatives so that they can be ranked them without solving the proposed model, and apply this new method to an MADM problem taken from the literature.Este trabajo forma parte del proyecto de investigación: MEC-FEDER Grant ECO2016-77900-P

Asejärjestelmien kustannustehokkuuden arviointi simulointi- ja systeemianalyysimenetelmin

Cost-effectiveness evaluation of weapon systems is needed to support acquisition planning of new systems to produce well-grounded allocation of resources to achieve the impact requirements. Evaluation of cost-effectiveness is often complicated by presence of multiple impact criteria, which may depend on other systems used and the operating situation. The cost-effectiveness analysis of weapon systems supports producing recommendations on how resources should be allocated between the acquisition of new systems and the service and maintenance of previously acquired systems. We develop methodologies based on portfolio and scenario analysis for the costeffectiveness evaluation of weapon systems to support acquisition planning. The cost-effectiveness of weapon system combinations (i.e. portfolios) is evaluated at different budget levels with regard to several impact criteria in multiple scenarios. The information about the impacts of weapon systems is captured from an independent battle simulator, which allows taking into account the interdependencies among weapon systems. The developed methodology admits incomplete information on the evaluation data and also multiple interpretations of impact criteria's importance in different scenarios. The developed methodology is applied in the cost-effectiveness evaluation of artillery systems, where impact data is captured from Sandis battle simulator developed by Finnish Defence Forces. The full text is in Finnish.Cost-effectiveness evaluation of weapon systems Cost-effectiveness evaluation of weapon systems is needed to support acquisition planning of new systems to produce well-grounded allocation of resources to achieve the impact requirements. Evaluation of cost-effectiveness is often complicated by presence of multiple impact criteria, which may depend on other systems used and the operating situation. The cost-effectiveness analysis of weapon systems supports producing recommendations on how resources should be allocated between the acquisition of new systems and the service and maintenance of previously acquired systems. We develop methodologies based on portfolio and scenario analysis for the costeffectiveness evaluation of weapon systems to support acquisition planning. The cost-effectiveness of weapon system combinations (i.e. portfolios) is evaluated at different budget levels with regard to several impact criteria in multiple scenarios. The information about the impacts of weapon systems is captured from an independent battle simulator, which allows taking into account the interdependencies among weapon systems. The developed methodology admits incomplete information on the evaluation data and also multiple interpretations of impact criteria's importance in different scenarios. The developed methodology is applied in the cost-effectiveness evaluation of artillery systems, where impact data is captured from Sandis battle simulator developed by Finnish Defence Forces. Artikkeli on suomeksi

A fuzzy AHP multi-criteria decision-making approach applied to combined cooling, heating and power production systems

Most of the real-world multi-criteria decision-making (MCDM) problems contain a mixture of quantitative and qualitative criteria; therefore quantitative MCDM methods are inadequate for handling this type of decision problems. In this paper, a MCDM method based on the Fuzzy Sets Theory and on the Analytic Hierarchy Process (AHP) is proposed. This method incorporates a number of perspectives on how to approach the fuzzy MCDM problem, as follows: (1) combining quantitative and qualitative criteria (2) expressing criteria pair-wise comparison in linguistic terms and performance of the alternative on each criterion in linguistic terms or exact values when criterion is qualitative or quantitative, respectively, (3) converting all the assessments into trapezoidal fuzzy numbers, (4) using the difference minimization method to calculate the local weight of criteria, employing the algebraic operations of fuzzy numbers based on the concept of α-cuts, (4) calculating the global weight of criteria and the global performance of each alternative using geometric mean and the weighted sum, respectively, (5) using the centroid method to rank the alternatives. Finally, an illustrative example on evaluation of several combined cooling, heat and power production systems is used to demonstrate the effectiveness of the proposed methodology

Artificial Neural Network Representations for Hierarchical Preference Structures

In this paper, we introduce two artificial neural network formulations that can be used to predict the preference ratings from the pairwise comparison matrices of the Analytic Hierarchy Process (AHP). First, we introduce a modified Hopfield network that can be used to exactly determine the vector of preference ratings associated with a positive reciprocal comparison matrix. The dynamics of this network are mathematically equivalent to the power method, a widely used numerical method for computing the principal eigenvectors of square matrices. However, we show that the Hopfield network representation is incapable of generalizing the preference patterns, and consequently is not suitable for approximating the preference ratings if the preference information is imprecise. Then we present a feed-forward neural network formulation that does have the ability to accurately approximate the preference ratings. A simulation experiment is used to verify the robustness of the feed-forward neural network formulation with respect to imprecise pairwise judgments. From the results of this experiment, we conclude that the feed-forward neural network formulation appears to be a powerful tool for analyzing discrete alternative multicriteria decision problems with imprecise or fuzzy ratio-scale preference judgments

Participatory approaches to foresight and priority-setting in innovation networks

In innovation networks, participatory foresight activities can typically have several functions. They can be seen as a tool for supporting decision-making on science and technology (S&T) priorities, but they can also be expected to contribute to the structures of a network beyond the scope of decision making. Foresight activities are often limited by tight timeframes, budgets and they need to be synchronized with other S&T processes. In this setting there is a need for tools that reflect foresight process owners' visions on trade-offs between objectives that are more important than others, and goals that can be achieved, given relevant constraints. This thesis develops, deploys and analyzes decision analytic methodologies for participatory foresight and priority-setting. The methodology enables foresight managers to adjust their foresight process to serve multiple goals and place emphasis on the objectives that are seen as most important. Foresight processes can be adjusted to meet the desired objectives by i) selecting a suitable "unit of analysis" for the analysis and discussion, ii) defining an appropriate composition of stakeholders for the different phases of the process, iii) different uses of decision analytic methodologies and iv) varying emphases on internet surveys, decision analysis, and face-to-face workshops. This thesis consists of six articles, where variants of the methodology are applied in different contexts. The articles include reflections from foresight activities carried out in support of management processes in Finnish industry clusters and in international research programs. They also include case studies from public S&T policy making, supporting the identification of small niche areas as well as providing input for decision-making on national innovation policies

Nuclear emergency decision support : a behavioural OR perspective

Operational researchers, risk and decision analysts need consider many behavioural issues. Despite many OR applications in nuclear emergency decision support, the literature has not paid sufficient attention to behavioural matters. In working on designing decision support processes for nuclear emergency management, we have encountered many behavioural issues. In this paper we synthesise the findings in the literature with our experience and identify a number of behavioural challenges to nuclear emergency decision support. In addition to challenges in model-building and interaction, we pay attention to a behavioural issue that is often neglected: the analysis itself and the communication of its implications may have behavioural consequences. We introduce proposals to address these challenges. First, we propose the use of models relying on incomplete preference information, outlining a framework and illustrating it with data from a previous decision analysis for the Chernobyl Project. Moreover, we reflect on the responsibility that rests on the analyst in addressing behavioural issues sensitively in order to lessen the effects on public stress. In doing so we make a distinction between System 1 Societal Deliberation and System 2 Societal Deliberation and discuss how this can help structure societal deliberation in the context of nuclear emergencies