Abstract
This paper studies the Facility Layout Problem (FLP) of a first tier supplier in the automotive industry. This complex manufacturing system involves multiple facilities, complex products, and layout reconfiguration constraints. One of the key requirements of this particular system is the need for high levels of flexibility in the reconfiguration of the layouts. This problem is formulated as a mixed-integer programming (MIP), based on a FLP model with multiple objectives and unequal areas. The model allows for two reconfiguration types: small and large changes. We explore the application of optimization methodologies to produce efficient and flexible layouts.

Abstract
In our living, we often have a sense of being tired due to a mental or physical work, plus a feeling of performance degradation even in the accomplishment of simple tasks. However, these mental states are often not consciously felt or are ignored, an attitude that may result in human failures, errors and even in the occurrence of health problems or on a decrease in the quality of life. States of fatigue may be detected with a close monitoring of some indicators, such as productivity, performance or even the health states. In this work it is proposed a model and a prototype to detect and monitor fatigue based on some of these items. We focus specifically on mental fatigue, a key factor in an individual's performance. With this approach we aim to develop leisure and work context-aware environments that may improve the quality of life and the individual performance of any human being.

Abstract
There has been a longstanding interest in deriving conditions under which dynamic optimization problems are normal, that is, the necessary conditions of optimality (NCO) can be written with a nonzero multiplier associated with the objective function. This paper builds upon previous results on nondegenerate NCO for trajectory constrained optimal control problems to provide even stronger, normal forms of the conditions. The NCO developed may address problems with nonsmooth, less regular data. The particular case of calculus of variations problems is here explored to show a favorable comparison with existent results.

Abstract
It has been a decade since a landmark piece of work on child well-being measurement based on a summary index was developed in the United States, the Index of Child and Youth Well-Being. Several research studies, both in the U.S. and Europe, followed on from this work. Despite these studies' valuable contribution, scope exists for further improvements at the methodological level. In the present paper we draw the methodological basis for a new, micro-based summary child well-being index in which children's views on their own well-being assume a central role and distinct weights (based on the children's perceptions) to each component that is included in the index are used. Based on 914 pairs of responses of Portuguese children and their carers, the newly proposed index was tested vis-A -vis other methodologies. The econometric estimations show that the significance of all potential well-being determinants (e.g., age, school cycle, mother's and father's level of education) remains the same across the distinct methods of calculation of child well-being indexes. However, the consideration of subjective components (degrees of importance and weights) allowed to evidence that the most relevant determinants of child well-being are the set of variables related to the child's parents, namely education and professional status. In particular, when compared to their counterparts, children whose fathers have higher education degrees reveal an increased overall well-being by around 25 %, whereas children whose fathers are unemployed present a decreased well-being by around 11 %.

Abstract
On the last decade Poker has been one of the most interesting subjects for artificial intelligence, because it is a game that requires game playing agents to deal with an incomplete information and stochastic scenario. The development of Poker agents has seen significant advances but it is still hard to evaluate agents' performance against human players. This is either because it is illicit to use agents in online games, or because human players cannot create agents that play like themselves due to lack of knowledge on computer science and/or AI. The purpose of this work is to fill the gap between poker players and AI in Poker by allowing players without programming skills to build their own agents. To meet this goal, a high-level language of poker concepts - PokerLang -was created, whose structure is easy to read and interpret for domain experts. This language allows for the quick definition of an agent strategy. A graphical application was also created to support the writing of PokerLang strategies. To validate this approach, some Poker players created their agents using the graphical application. Results validated the usability of the application and the language that supports it. Moreover, the created agents showed very good results against agents developed by other experts.

Abstract
We analysed the community structure of a network of news clips where relationships were established by the co-reference of entities in pairs of clips. Community detection was applied to a unidimensional version of the news clips network, as well as to a multidimensional version where dimensions were defined based on three different classes of entities: places, people, and dates. The goal was to study the impact on the quality of the identified community structure when using multiple dimensions to model the network. We did a two-fold evaluation, first based on the modularity metric and then based on human input regarding community semantics. We verified that the assessments of the evaluators differed from the results provided by the modularity metric, pointing towards the relevance of the utility and network integration phases in the identification of semantically cohesive groups of news clips. Copyright © 2013 Inderscience Enterprises Ltd.