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A model of traveller behaviour should recognise the exogenous and endogenous factors that limit the choice set of users. These factors impose constraints on the decision maker, which constraints may be considered implicitly, as soft constraints imposing thresholds on the perception of changes in attribute values, or explicitly as hard constraints. The purpose of this paper is twofold: (1) To present a constrained nested logit-type choice model to cope with hard constraints. This model is derived from the entropymaximizing framework. (2) To describe a general framework to deal with (dynamic) nonlinear utilities. This approach is based on Reproducing Kernel Hilbert Spaces. The resulting model allows the dynamic aspect and the constraints on the choice process to be represented simultaneously. A novel estimation procedure is introduced in which the utilities are viewed as the parameters of the proposed model instead of attribute weights as in the classical linear models. A discussion on over-specification of the proposed model is presented. This model is applied to a synthetic test problem and to a railway service choice problem in which users choose a service depending on the timetable, ticket price, travel time and seat availability (which imposes capacity constraints). Results show (1) the relevance of incorporating constraints into the choice models, (2) that the constrained models appear to be a better fit than the counterpart unconstrained choice models; and (3) the viability of the approach, in a real case study of railway services on the Madrid-Seville corridor (Spain).

This paper presents an application of diverse soft-computing techniques to adaptive traffic light controls. The proposed methodology consists of two main phases: off-line and on-line. First, clustering techniques and optimization methods are used at the off-line stage to discover the prototypes which characterize the traffic mobility patterns at an intersection. After this process an optimum timing plan is decided for each mobility pattern detected. In the on-line phase, a prediction model is then constructed on the basis of the prototypes found. Fuzzy Logic based techniques are used to formally represent the prototypes in the prediction model and these prototypes are parametrically defined through frameworks. During the on-line phase an intelligent transportation system, by using the prediction model, matches the current traffic conditions to the mobility patterns detected at the off-line stage in order to identify the most suitable one to be used. The use of these techniques supposes a substantial contribution to the significance of the prediction model, making it robust in the face of anomalous mobility patterns, and efficient from the point of view of real-time computation.

The evaluation of the players' performance in sports teams is commonly based on the opinion of experts who do not always agree on the importance of the chosen indicators. This paper presents a novel approach based on fuzzy multi-criteria group decision-making tools for selecting those criteria that best represent the handball player's performance in a match and for setting their relevance weights. Our approach consists of a fuzzy model to aggregate expert judgments. This methodology overcomes some drawbacks of classical systems, including the definition of the relevance of each criteria using linguistic labels. A preliminary evaluation analyzes handball players' performance indicators and their application to a short tournament. Considering the obtained results, we can conclude that the proposal is relevant and provides useful insights regarding player performance in different matches. The proposed methodology has also been compared with a basic plus-minus rating methodology. This comparison illustrates the feasibility of our approach. Results suggest that plus-minus rating is not the best solution to represent the performance of specialized players who only play when their team attack or defense. Our approach demonstrates being more appropriate for sports such as handball because it includes the valuation of a full set of positive actions in defense and attack.

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