SAP- Modular Tool for Specification and Analysis of User Preferences in Multiple-Criteria Model Analysis

Model based Decision Support Systems (DSS) often use multiple-criteria optimization for selecting Pareto-efficient solutions. Such a selection is based on interactive specification of user preferences. This can be done by specification of aspiration and reservation levels for criteria. Diverse graphical user interface could be used for specification of these levels as well as for interpretation of results. In the approach presented in this paper the specified aspiration and reservation levels are used for generation of component achievement functions for corresponding criteria. Such functions can be interpreted as fuzzy membership functions or as functions, which reflect the degree of satisfaction with given values of criteria. The paper outlines the methodological background and modular structure of a DSS shell for multiple-criteria analysis of decision problems that can be represented as Linear Programming (LP) or Mixed Integer Programming (MIP) problems. The DSS shell has been used at IIASA for analysis of decision problems in water quality management and land use for sustainable development planning. The pilot implementation of one component of that DSS, namely the modular software tool for interactive specification of user preferences is described in more detail. The tool has been also used as in a DSS for analysis of non-linear problems in several engineering applications

Multicriteria Methodology for the NEEDS Project

This report begins with an overview of multicriteria analysis methods, and the basic principles of developing mathematical models for such analysis. An overview of various representation of user preferences is then presented, including methods based on pairwise comparisons of criteria and those based on scalarizing functions. This is followed by a summary of structures of criteria and alternatives. Next, basic properties of multi-criteria analysis are discussed, followed by a more detailed presentation of the similarities of and differences between the main methods based on scalarizing functions. This report concludes that existing methods do not best meet the needs of the NEEDS project, presents the reasons, and proposes a new methodology for development. Depending upon the development and testing of this new methodology, an existing method will also be chosen as a backup for comparative or alternate use

Multicriteria Methodology for the NEEDS Project

This report begins with an overview of multicriteria analysis methods, and the basic principles of developing mathematical models for such analysis. An overview of various representation of user prefereces is then presented, including methods based on pairwise comparisons of criteria and those based on scalarizing functions. This is followed by a summary of structures of criteria and alternatives. Next, basic properties of multi-criteria analysis are discussed, followed by a more detailed presentation of the similarities of and differences between the main methods based on scalarizing function. This report concludes that existing methods do not best meet the needs of the NEEDS project, presents the reasons, and proposes a new methodology for development. Depending upon the development and testing of this new methodology, an existing method will also be chosen as a backup for comparative or alternate use

Objective measurement of habitual sedentary behavior in pre-school children: comparison of activPAL with actigraph monitors

The Actigraph is well established for measurement of both physical activity and sedentary behavior in children. The activPAL is being used increasingly in children, though with no published evidence on its use in free-living children to date. The present study compared the two monitors in preschool children. Children (n 23) wore both monitors simultaneously during waking hours for 5.6d and 10h/d. Daily mean percentage of time sedentary (nontranslocation of the trunk) was 74.6 (SD 6.8) for the Actigraph and 78.9 (SD 4.3) for activPAL. Daily mean percentage of time physically active (light intensity physical activity plus MVPA) was 25.4 (SD 6.8) for the Actigraph and 21.1 (SD 4.3) for the activPAL. Bland-Altman tests and paired t tests suggested small but statistically significant differences between the two monitors. Actigraph and activPAL estimates of sedentary behaviour and physical activity in young children are similar at a group level

User Guide to MCA: Multiple Criteria Analysis of Discrete Alternatives with a Simple Preference Specification

This report provides detailed information about using the MCA, which is the Web-based application formultiple criteria analysis of discrete alternatives with a simple preference specification. MCA in its currently available version supports analysis of a set of discrete alternatves, defined either interactively or through a prepared file. Each alternative is characterized by several attributes (indicators) that serve for specification of criteria. MCA has been designed for problems having large numbers of alternatives and of criteria. However, it can also be used for problems with small numbers of criteria and/or alternatives. The report is composed of two main parts. The first one provides an overview of the MCA and summarize the methodology of multiple criteria analysis implemented in the MCA. The second part consists of the step-by-step detailed tutorial to the MCA organized into three stages corresponding to (1) basic funtions of the MCA, (2) specification of problems, instances, and analyses, and (3) interactive multiciteria analysis process

Overview of Methods Implemented in MCA: Multiple Criteria Analysis of Discrete Alternatives with a Simple Preference Specification

Many methods have been developed for multiple criteria analysis and/or ranking of discrete alternatives. Most of them require complex specification of preferences. Therefore, they are not applicable for problems with numerous alternatives and/or criteria, where preference specification by the decisin makers can hardly be done in a way acceptable for small problems, e.g., for pair-wise comparisons. In this paper we describe several new methods implemented for a real-life application dealing with multi-criteria analysis of future energy technologies. This analysis involves large numbers of both alternatives and criteria. Moreover, the analysis was made by a large number of stakeholders without expeience in analytical methods. Therefore a simple method for interactive preference specification was condition for the analysis. The paper provides overview of several of new methods based on diverse concepts developed for multicriteria analysis, and summarizes a comparison of methods and experence of using them

Multiple Criteria Analysis of Discrete Alternatives with a Simple Preference Specification: Pairwise-outperformance based Approaches

Many methods have been developed for multiple criteria analysis and/or ranking of discrete alternatives. Most of them require complex specification of preferences. Therefore, they are not applicable for problems with numerous alternatives and/or criteria, where preference specification by the decision makers can hardly be done in a way acceptable for small problems, e.g., for pair-wise comparisons. In this paper we describe several new methods implemented for a real-life application dealing with muti-criteria analysis of future energy technologies. This analysis involves large numbers of both altrnatives and criteria. Moreover, the analysis was made by a large number of stakeholders without expeience in analytical methods. Therefore, a simple method for interactive preference specification was a condition for the analysis. The paper presents a number of new methods based on the developed out performance aggregations that take into account inter-alternative factors. Finally, a comparison of methods and experience of using them is discussed

AEZWIN An Interactive Multiple-Criteria Analysis Tool for Land Resources Appraisal

Since the early 1980's, the Food and Agriculture Organization of the United Nations (FAO) and the International Institute for Applied Systems Analysis (IIASA) have been collaborating on expanding FAO's Agro-Ecological Zones (AEZ) methodology of land resources appraisal by incorporating decision support tools for optimizing the use of land resources. Agro-ecological zoning involves the inventory, characterization and classification of the land resources for assessments of the potential of agricultural production systems. The characterization of land resources includes components of climate, soils and land form, basic for the supply of water, energy, nutrients and physical support to plants. When evaluating the performance of alternative land utilization types, often the specification of a single objective function does not adequately reflect the preferences of decision-makers, which are of multi-objective nature in many practical problems dealing with resources. Therefore interactive multicriteria model analysis (MCMA) has been applied to the analysis of AEZ models. A user friendly interface has been developed and documented in order to permit use of the software by persons with only very basic computing experience. The methodology of MCMA is illustrated in the companion paper by a detailed tutorial example

IAC-DIDAS-N - A Dynamic Interactive Decision Analysis and Support System for Multicriteria Analysis of Nonlinear Models, v.4.0

This paper presents introductive and user documentation -- including extended summary, theoretical manual, short user manual and description of illustrative examples -- for a version of decision analysis and support systems of DIDAS family that is designed for multicriteria analysis of nonlinear models on professional microcomputers. This version has been developed in the years 1986-1990 in the Institute of Automatic Control, Warsaw University of Technology, under a joint research program with the Systems and Decision Sciences Program of IIASA. It can be run on professional microcomputers compatible with IBM-PC-XT or AT (with Hercules Graphics Card, Color Graphics Adapter or Enhanced Graphics Adapter and, preferably, with a numeric coprocessor and a hard disk) and supports graphical representation of results of interactive multicriteria analysis. Moreover, this version called IAC-DIDAS-N is provided with a new nonlinear model generator and editor that support, in an easy standard of a spreadsheet, the definition, edition and symbolic differentiation of nonlinear substantive models for multiobjective decision analysis. A specially introduced standard of defining nonlinear programming models for multiobjective optimization helps to connect the model generator with other parts of the system. Optimization runs involved in interactive, multiobjective decision analysis are performed by a solver, that is, a version of nonlinear programming algorithm specially adapted for multiobjective problems. This algorithm is based on shifted penalty functions and projected conjugate directions techniques similarly as in former nonlinear versions of DIDAS, but it was further developed and several improvements were added. The system is permanently updated and developed. Currently (starting from October 1990) the version 4.0 of the system is released. Most of enhancements added in this version are not directly visible to the user. They influence the efficiency of the system