Abstract
In this paper we present a hybrid approach to integrative clustering based on the p-median problem with clients' preferences. We formulate the problem of simultaneous clustering of a set of objects, characterized by two sets of features, as a bi-level p-median model. An exact approach involving a branch-and-cut method combined with the simulated annealing algorithm is used, that allows one to find a two-source clustering. The proposed approach is compared with some well-known mathematical optimisation based clustering techniques applied to the NCI-60 tumour cell line anticancer drug screen dataset. The results obtained demonstrate the applicability of our approach to find competitive integrative clusterings. Copyright © by the paper's authors.

Abstract
This study proposes an optimization model to improve the robustness of an existing bus schedule. Robustness represents the ability of schedules to absorb deviations from the timetable and to prevent their propagation through the daily operations. The model developed proposes an optimal assignment of arrival times and distribution of slacks among Time Control Points of a bus line, in order to minimize delays and anticipations from schedule. This required the use of data collected through GPS devices installed in buses, informing the location of buses during their daily operation. The robustness of bus schedules was evaluated through the quantification of delays and anticipations of real observations of bus shifts by comparison with the timetable. The performance measures used to evaluate robustness are the average delay (or anticipation) of buses by comparison with the timetable, and the probability that a passenger that arrives on time according to the timetable will miss the bus or have to wait more than a specified threshold at a Time Control Point. We also compared the improvement of the schedule proposed by the optimization model with the original schedule. The results obtained in a real-world case study, corresponding to a bus line operating in Porto, showed that the model could return an improved schedule for all performance measures considered when compared with the original schedule.

Abstract
The United States, Brazil, and Argentina are responsible for 83% of world’s soybean production. Together, they respond to more than 80% of soybean grains and soybean meal exported and for more than 60% of soybean oil exportation. This paper studies the soybean trade of these three major exporters with the top ten commercial partners of each one in order to examine the main factors that influence this relationship. We follow a network analysis approach to evaluate the level of interdependence between exporters and importers. Our research studies the three main soybean products: grain, meal, and oil. The findings seem to indicate that countries prefer importing soybean grains to process inside their borders due to commodity prices and logistics costs.

Abstract
Contemporary urban transportation networks are facing challenges to address the growing needs of mobility, all the while improving their economic gains and environmental sustainability. Several studies demonstrate that competitive alternatives to individual private transport are able to address these challenges, such as public transportation services. Thus, the need for optimising their operational efficiency and offer user-centric service delivery arises, with a range of challenges related to the inherent complexity of urban transportation networks as well as the range of dynamic elements involved in such systems. An innovative approach to this problem leverages personal mobile devices in combination with collaborative exchange of information. In this study a system was developed to combine information provided by travellers with data from public transport operators. The result is a rich model of the transportation network that enables the distribution of information in a personalized way and in real-time: the Seamless Mobility solution. Large-scale and expensive infrastructures, such as existing ticketing systems, constitute a threat to such flexibility and traveller access to services. As a result, a distributed architecture was targeted with the goal of integrating personal mobile devices in the infrastructure, with benefits for travellers and transport operators. The proposed solution integrates a broad scope of challenges, including application of secure mobile payments methods, data aggregation from different components and distribution based on relevance techniques. With the implementation of this solution we expect to positively impact the way travellers and transport operators interact, and contribute towards mobility services that are more agile and adequate, taking into account that mobility patterns vary from person to person, seasonally, and even throughout a day. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
This paper proposes an ontology-based approach to visualizing urban mobility data. Our approach, which is in ongoing development, is centered in a visualization-oriented urban mobility ontology that is used to semantically characterize data and visualization techniques. We present a practical application to a public transportation network of the city of Porto, Portugal. We address how semantics can empower and facilitate tasks like automatic recommendation of visualization techniques, and definition of a data filter based on passengers' journey patterns.

Abstract
This paper develops an innovative methodology to assess municipal performance concerning the environmental efficiency of new buildings construction, focusing on the consumption of different types of materials. This study aims to support local governments in the definition of policies for improvements in service provision based on the results of a benchmarking study. The methodology developed includes two stages. The first step concerns the evaluation of municipal environmental efficiency using Data Envelopment Analysis and the identification of factors that may explain different levels of performance. The second step enables the classification of municipalities in terms of the efforts required to achieve environmental efficiency. For this purpose, we used clustering analysis, namely the k-means algorithm. To illustrate the methodology developed, we analyzed the data of the major materials used in the construction of new buildings (metals, non-metallic minerals, fossil fuels, and biomass) in the municipalities of Lisbon metropolitan area between 2003 and 2009. The study revealed that the environmental efficiency of new buildings construction varies considerably among municipalities, suggesting a high potential for performance improvement.