Abstract
This paper presents an innovative approach to solve the product-launch planning problem in the pharmaceutical industry, with uncertainty on the product demand and on clinical trials. A mixed integer linear programming (MILP) model, incorporating Monte Carlo simulation (MCS), was developed for optimizing the process design (process-unit allocation and scale-up decisions) and for capacity planning (acquisition of new units), considering the products that still require development, and the products that are already in commercialization. MCS is performed in a two-step procedure, based on Normal and Bernoulli distributions, in order to capture the effects of demand variability and trials pass-fail uncertainty, respectively. Product-launch decisions are made taking into account the probability distributions of alternative process designs, of new capacity requirements, and of the coefficients of the objective function. The applicability of the proposed solution approach is demonstrated in an illustrative case study.

Abstract
Software engineering (SE) is an area with a wide range of concepts and knowledge. Such diversity of topics, requires the application of different teaching and learning techniques for an effective education. Serious Games is one of such techniques, yet its design tends to be complex, currently lacking a map of game design standards that comply with SE education requirements. This paper presents a process to identify the game design patterns that can be effective for teaching software engineering, specifically the software project management topic. Firstly, it begins by identifying the relationship between game design patterns and teaching and learning functions based on literature review. Secondly, it filters which of those teaching and learning functions is most relevant to software project management education, according to SE education specialists. Finally, it validates the relationship between game design patterns and software project management education through an empirical study conducted with master students. The results can be used as a basis for designing and developing serious games for teaching software project management. (C) 2016 The Authors. Published by Elsevier Ltd.

Abstract
This paper presents work-in-progress of the POSTDATA project. This project aims to provide means to solve the interoperability issues that exist among the digital poetry repertoires. These repertoires hold data of poetry metrics that is locked in their own databases and it is not freely available to be compared and to be used by intelligent machines that could infer over the data. The POSTDATA project will use Linked Open Data (LOD) technologies to overcome the interoperability problems. POSTDATA is developing a metadata application profile (MAP) for the digital poetry repertoires, a construct that enhances interoperability. This development follows the method for the development of MAP (Me4MAP). A MAP for the digital poetry repertoires will open doors for these repertoires to be able to structure the data with a common model in order to publish it as Linked Open Data. This paper presents how this MAP is being developed so far.

Abstract
This book gathers carefully selected works in Mathematical Economics, on myriad topics including General Equilibrium, Game Theory, Economic Growth, Welfare, Social Choice Theory, Finance. It sheds light on the ongoing discussions that have brought together leading researchers from Latin America and Southern Europe at recent conferences in venues like Porto, Portugal; Athens, Greece; and Guanajuato, Mexico. With this volume, the editors not only contribute to the advancement of research in these areas, but also inspire other scholars around the globe to collaborate and research these vibrant, emerging topics.

Abstract
Although wind power generation has extended a maturity in technology, there are still many concerns regarding the optimal support of regulatory bodies for renewable resources. In this context, the regulatory body should form a market structure or consider market rules and regulations to not only attract investors to renewable power plants, but also provide an efficient market that reflects a safe and clear competition environment. In this paper, an agent-based game-theoretic model is developed to investigate the electricity market behavior under oligopoly circumstances. The proposed model reveals the potential of collusive and strategic behavior of market participants. By employing the proposed model, impacts of different supportive schemes on the behavior of the wind power producer and conventional thermal units are investigated. According to the results obtained, if the regulatory bodies do not consider strategic collusion of market participants, adverse consequences for wind power producers might happen in the long-term horizon.

Abstract
This paper presents a framework and methods to estimate electric vehicles' possible states, regarding their demand, location and grid connection periods. The proposed methods use the Monte Carlo simulation to estimate the probability of occurrence for each state and a fuzzy logic probabilistic approach to characterize the uncertainty of electric vehicles' demand. Day-ahead and hour-ahead methodologies are proposed to support the smart grids' operational decisions. A numerical example is presented using an electric vehicles fleet in a smart city environment to obtain each electric vehicle possible states regarding their grid location.