In this paper we introduce the class of axial solutions for multiple objective optimization problems in contexts in which partial information on preference weights is available. These solutions combine the use of an improvement axis to direct the search of the most preferred result with the...

In this paper we study cooperative games with fuzzy payoffs. The main advantage of the approach presented is the incorporation into the analysis of the problem of ambiguity inherent in many real-world collective decision situations. We propose extensions of core concepts which maintain the fuzzy...

In this paper, a generalization of the linear production model is considered on the basis of a DEA-inspired technology in which the maximization of the production levels is formulated as a multi-objective linear programming problem. When multiple decision-makers cooperate by pooling their...

It is shown that the Harsanyi NTU solution is consistent according to the Hart and Mas-Colell reduced game for NTU games, when we consider payoff configurations as solution outcomes. Moreover, we characterize this solution on a wide class of NTU games where this solution is single-valued:...

Macaulay duration matched strategy is a key tool in bond portfolio immunization. It is well known that if term structures are not flat or changes are not parallel, then Macaulay duration matched portfolio can not guarantee adequate immunization. In this paper the approximate duration is proposed...

This paper discusses the use of dynamic modelling in consumer credit risk assessment. It surveys the approaches and objectives of behavioural scoring, customer scoring and profit scoring. It then investigates how Markov chain stochastic processes can be used to model the dynamics of the...

This paper discusses the similarities and differences in the collection process between in-house and 3rd party collection. The objective is to show that, although the same type of modelling approach to estimating the Loss Given Default (LGD) can be used in both cases, the details will be...