Abstract
In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012

Abstract
Purpose - The purpose of this paper is to present a CAD-based human-robot interface that allows non-expert users to teach a robot in a manner similar to that used by human beings to teach each other. Design/methodology/approach - Intuitive robot programming is achieved by using CAD drawings to generate robot programs off-line. Sensory feedback allows minimization of the effects of uncertainty, providing information to adjust the robot paths during robot operation. Findings - It was found that it is possible to generate a robot program from a common CAD drawing and run it without any major concerns about calibration or CAD model accuracy. Research limitations/implications - A limitation of the proposed system has to do with the fact that it was designed to be used for particular technological applications. Practical implications - Since most manufacturing companies have CAD packages in their facilities today, CAD-based robot programming may be a good option to program robots without the need for skilled robot programmers. Originality/value - The paper proposes a new CAD-based robot programming system. Robot programs are directly generated from a CAD drawing "running" on a commonly available 3D CAD package (Autodesk Inventor) and not from a commercial, computer aided robotics (CAR) software, making it a simple CAD integrated solution. This is a low-cost and low-setup time system where no advanced robot programming skills are required to operate it. In summary, robot programs are generated with a high-level of abstraction from the robot language.

Abstract
Smart grids consist of millions of automated electronic meters that will be installed in electricity distribution networks and connected to servers that will manage grid supervision, billing and customer services. World sustainability regarding energy management will definitely rely on such grids, so smart grids need also to be sustainable themselves. This sustainability depends on several research problems that emerge from this new setting (from power balance to energy markets) requiring new approaches for knowledge discovery and decision support. This paper presents a holistic distributed stream clustering view of possible solutions for those problems, supported by previous research in related domains. The approach is based on two orthogonal clustering algorithms, combined for a holistic clustering of the grid. Experimental results are included to illustrate the benefits of each algorithm, while the proposal is discussed in terms of application to smart grid problems. This holistic approach could be used to help solving some of the smart grid intelligent layer research problems, thus improving global sustainability.

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Lenses are one of the most popular approaches to define bidirectional transformations between data models. However, writing a lens transformation typically implies describing the concrete steps that convert values in a source schema to values in a target schema. In contrast, many XML-based languages allow writing structure-shy programs that manipulate only specific parts of XML documents without having to specify the behavior for the remaining structure. In this paper, we propose a structure-shy bidirectional two-level transformation language for XML Schemas, that describes generic type-level transformations over schema representations coupled with value-level bidirectional lenses for document migration. When applying these two-level programs to particular schemas, we employ an existing algebraic rewrite system to optimize the automatically-generated lens transformations, and compile them into Haskell bidirectional executables. We discuss particular examples involving the generic evolution of recursive XML Schemas, and compare their performance gains over non-optimized definitions. © 2012 Springer-Verlag.