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

Life cycle impact assessment based on decision analysis

Life cycle assessment (LCA) is a popular tool for evaluating environmental impacts of products and services. However, the methodological choices and framework to assess environmental impacts in LCA are still under discussion. Despite intensive development worldwide, few attempts have been made hitherto to systematically present the theoretical bases of life cycle impact assessment (LCIA). In this study, the decision analytic foundations for LCIA are illustrated. It is shown that the typical aggregation equation used in LCIA for calculating indicator results can be derived from multiattribute value theory (MAVT) if certain simple assumptions hold. The decision analysis framework presented in this work offers additional values for all the phases of LCIA. A value tree, a tool used for structuring multicriteria decision making problems, can be helpful for selection of impact categories and classification. MAVT can clarify the debate concerning marginal and average approaches in the determination of characterisation factors. On the basis of MAVT, normalisation is needed before weighting. The methods and experiences of preference elicitation derived from the field of decision analysis can be utilised in the determination of subjective characterisation factors and impact category weights. Furthermore, experiences and techniques for the sensitivity analysis of multi-criteria decision models can be utilised in LCIA. In addition, MAVT assists in the calculation of impact category indicator results and total impact indicator results according to the appropriate aggregation equations. The decision analysis framework presented in this work is flexible and suitable for different impact assessment approaches developed in LCIA and it can help the methodological development with which the non-linearity aspects of impact assessment are taken into account. It is shown in the work that site-dependent characterisation methods can easily be fitted into the framework. In a case study of the Finnish forest industry a Finland-specific impact assessment model utilising the results of other tools, such as air quality and transport models and even expert judgements, was developed. In addition, the so-called ratio estimation method for the elicitation of impact category weights was applied and developed so that interval-valued ratio judgements could be used in the uncertainty analysis of the model. In the case of the Finnish metals industry, decision analysis impact assessment was applied to produce a solution in which global, regional and local environmental problems were assessed in the same framework. In both case studies, experts working with the environmental issues valuated impact category weights with the help of decision analysis techniques. In the work it was shown that MAVT provides a foundation for a logical and rational approach to impact assessment in LCA. In the future, there is a need to demonstrate quantitatively the differences between LCIA conducted according to MAVT and according to current practices. Furthermore, there is a need for research to study the strengths and weaknesses of the different decision analysis methods for LCIA purposes.reviewe

Multi-Attribute Decision Tree Evaluation in Imprecise and Uncertain Domains

Abstract We present a decision tree evaluation method integrated with a common framework for analyzing multi-attribute decisions under risk, where information is numerically imprecise. The approach extends the use of additive and multiplicative utility functions for supporting evaluation of imprecise statements, relaxing requirements for precise estimates of decision parameters. Information is modeled in convex sets of utility and probability measures restricted by closed intervals. Evaluation is done relative to a set of rules, generalizing the concept of admissibility, computationally handled through optimization of aggregated utility functions. Pros and cons of two approaches, and tradeoffs in selecting a utility function, are discussed

Optimal pilot decisions and flight trajectories in air combat

The thesis concerns the analysis and synthesis of pilot decision-making and the design of optimal flight trajectories. In the synthesis framework, the methodology of influence diagrams is applied for modeling and simulating the maneuvering decision process of the pilot in one-on-one air combat. The influence diagram representations describing the maneuvering decision in a one sided optimization setting and in a game setting are constructed. The synthesis of team decision-making in a multiplayer air combat is tackled by formulating a decision theoretical information prioritization approach based on a value function and interval analysis. It gives the team optimal sequence of tactical data that is transmitted between cooperating air units for improving the situation awareness of the friendly pilots in the best possible way. In the optimal trajectory planning framework, an approach towards the interactive automated solution of deterministic aircraft trajectory optimization problems is presented. It offers design principles for a trajectory optimization software that can be operated automatically by a nonexpert user. In addition, the representation of preferences and uncertainties in trajectory optimization is considered by developing a multistage influence diagram that describes a series of the maneuvering decisions in a one-on-one air combat setting. This influence diagram representation as well as the synthesis elaborations provide seminal ways to treat uncertainties in air combat modeling. The work on influence diagrams can also be seen as the extension of the methodology to dynamically evolving decision situations involving possibly multiple actors with conflicting objectives. From the practical point of view, all the synthesis models can be utilized in decision-making systems of air combat simulators. The information prioritization approach can also be implemented in an onboard data link system.reviewe

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

Building a Composite Indicator to Measure Environmental Sustainability Using Alternative Weighting Methods

Environmental sustainability in agriculture can be measured through the construction of composite indicators. However, this is a challenging task because these indexes are heavily dependent on how the individual base indicators are weighted. The main aim of this paper is to contribute to the existing literature regarding the robustness of subjective (based on experts’ opinions) weighting methods when constructing a composite indicator for measuring environmental sustainability at the farm level. In particular, the study analyzes two multi-criteria techniques, the analytic hierarchy process and the recently developed best-worst method, as well as the more straightforward point allocation method. These alternative methods have been implemented to empirically assess the environmental performance of irrigated olive farms in Spain. Data for this case study were collected from a panel of 22 experts and a survey of 99 farms. The results obtained suggest that there are no statistically significant differences in the weights of the individual base indicators derived from the three weighting methods considered. Moreover, the ranking of the sampled farms, in terms of their level of environmental sustainability measured through the composite indicators proposed, is not dependent on the use of the different weighting methods. Thus, the results support the robustness of the three weighting methods considered

Decision Analysis and Validation of Value Focused Thinking Decision Models Using Multivariate Analysis Techniques

Decision Analysis (DA) is a useful tool to assist decision makers (DM) with difficult and complex decisions using mathematical models. Value Focused Thinking (VFT) models are a useful DA tool widely employed in the Air Force. However, VFT models are rarely validated. This research will attempt to validate any given VFT model and provide insight into the discriminating attributes of the alternative set. First, a two group discriminant analysis is applied the alternative set given the prior knowledge of the selected alternatives. Next, compromise programming is used attempt to minimize the distance between the posterior probability of an alternative being selected and its current weighted value by varying the weights. This set of optimized weights is then used in the two group discriminant analysis to classify the alternative set and attempt to validate the VFT model by selecting the same subset of alternatives chosen by the DM. Additionally, this process will provide insight into what attributes of a given alternative set are actually the discriminating factors in the decision which may or may not be the attributes that are most important to or most heavily weighted by the DM

Towards a unified descriptive framework for industrial objective declaration and performance measurement

International audienceExpressing the performance of industrial companies is an important feature for their continuous improvement. As the performance concept refers to the objective one, our idea is to relate the performance expression mechanism to that of the objective declaration. We propose a variable tree framework to describe the break-down of objectives and the expression of the performances, highlighting the multicriteria aspect of both the performance and the objectives. Moreover, the temporal aspects of the objective declarations are emphasised, leading to the introduction of both the objective and the performance temporal trajectories. Such trajectories take into account the whole of the temporal horizon that is associated with the achievement of the objective. The link between the provided trees and trajectories is established through the elementary objective notion which corresponds to the leaves of the trees. A conventional recursive depth-first search algorithm is applied to the variable tree for the computation of the corresponding performances, at any considered milestone of the temporal horizon. Finally, the overall throughput time of the hydraulic cylinders manufacturing line of the Bosch Rexroth Company is considered to illustrate the proposed ideas

Continuous Decision Support

Organizations are often faced with portfolio construction efforts that require them to select one or more alternatives, subject to resource constraints, with the aim of achieving the maximum value possible. This is a well-defined problem with a number of analytically defensible approaches, provided the entire set of alternatives is known when the decision event takes place. Less well treated in the literature is how to approach this problem when the entire set of alternatives is unknown, as when the alternatives arrive over time. This change in the availability of data shifts the problem from one of identifying an optimal subset to one in which a series of smaller decisions are undertaken regarding the acceptability of each alternative as it presents itself. This work expands upon a methodology known as the Triage Method. The original Triage Method provided a screening tool that could be applied to alternatives as they presented themselves to determine if they should be accepted for further study, rejected out of hand, or held pending until later date. This decision was made strictly upon the value of the alternative and with no consideration of its cost. Two extensions to the Triage Method are offered which provide a capability to consider cost and other resource requirements of the alternatives, thus allowing a move from simply screening to portfolio selection. Guidelines are presented as to when each of these extensions is best employed, a characterization of the performance tradeoff between these and more traditional methodologies is developed, and insight and techniques for setting the value of parameters required by the extensions are provided