Bayesian Belief Nets (BBNs) have proven to be an extremely powerful technique for reasoning under uncertainty. We have used them in a range of real applications concerned with predicting properties of critical systems. In most of these applications we are interested in a single attribute of the system such as safety, reliability, or defect-density. Although such BBNs provide important support f...

When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. Th...

The fundamental problem underlying all multi-criteria decision analysis (MCDA) problems is that of dominance between any two alternatives: ‘Given two alternatives A and B, each described by a set criteria, is A preferred to B with respect to a set of decision maker (DM) preferences over the criteria?’. Depending on the application in which MCDA is performed, the alternatives may represent strat...

Page ii research, which may assist in negotiating sustainable decisions while fostering a collaborative learning process between DMs, experts and the community. The two uncertainty analysis approaches overcome the limitations of the existing sensitivity analysis methods by being applicable to multiple MCDA techniques, incorporating uncertainty in all of the input parameters simultaneously, iden...

BACKGROUND Estimating the value of medical treatments to patients is an essential part of healthcare decision making, but is mostly done implicitly and without consulting patients. Multi criteria decision analysis (MCDA) has been proposed for the valuation task, while stated preference studies are increasingly used to measure patient preferences. In this study we propose a methodology for using...

Supervised classification often consists in assigning a set of entities (e.g. alternatives, images, projects, subjects) into pre-defined and homogeneous categories. Categories are known a priori either by defining profiles limit between them or by a set of typical profiles (reference prototypes or elements) for each category. Ordinal Classification (or Sorting) usually refers to an order relati...

Despite the fact that the origins of the MCDM school lie in extensions of linear programming to problems with multiple objectives, multicriteria analysis, in particular methods for choosing between discrete alternatives, tend to be viewed by Operational Research/Management Science (OR/MS) practitioners as distinct from other methods of OR/MS. In this paper we argue that MCDA should be viewed as...

The aim of this paper is to convince the MultiCriteria Decision Aid (MCDA) and Preference Learning communities to investigate and to contribute in the development of methodologies dedicated to hospital ranking. To do so, we present the French hospital ranking and show how these rankings can be built properly through two existing methods: decision tree and ELECTRE Tri.

On Low-Envy Truthful Allocations p. 111 On Multi-dimensional Envy-Free Mechanisms p. 120 Stable Rankings in Collective Decision Making with Imprecise Information p. 132 Finding Best k Policies p. 144 Multiple Criteria Decision Analysis New Hybrid Recommender Approaches: An Application to Equity Funds Selection p. 156 A Prescriptive Approach for Eliciting Imprecise Weight Statements in an MCDA P...

Multicriteria decision analysis (MCDA) involves techniques which relatively recently have received great increase in interest for their capabilities of solving spatial decision problems. One of the most frequently used techniques of MCDA is Analytic Hierarchy Process (AHP). In the AHP, decision-makers make pairwise comparisons between different criteria to obtain values of their relative import...