Abstract
Considering the new paradigm in the industry, where clients request small amounts of a growing range of products, the times of crisis and the fierce competition for businesses survival, it is crucial for Organizations to be able to reduce the waste of raw materials. In the manufacturing industry, the waste of materials could be minimized with the introduction of decision support systems in the process. In this paper we propose an information system that enables the optimization of purchases and consumption of materials, promoting waste reduction and boosting profitability.

Abstract
Considering the new paradigm in the industry, where clients request small amounts of a growing range of products, the times of crisis and the fierce competition for businesses survival, it is crucial for Organizations to be able to reduce the waste of raw materials. This waste could be minimized with the introduction of decision support systems in the process. In this paper we propose an information system that enables the optimization of purchases and consumption of materials, promoting waste reduction and boosting profitability.

Abstract
This chapter presents the preliminary results of an IT organizational project management maturity research called OPM3® Portugal Project, which is currently underway. It was designed by Portuguese research and development organization Ambithus, based on PMI's (Project Management Institute) OPM3® (Organizational Project Management Maturity Model) standard. A descriptive analysis of IT organizations is made, the case studies selection criteria are explained, and a relevant literature revision of clustering models is made. Preliminary results from the IT organizations are presented and organized by Project Management and Portfolio Management processes, and Organizational Enablers. After the results analysis, it presents a list of processes and procedures that serves as the guidelines for what IT organizations need to improve to obtain a better level of maturity in Project Management. The overall results show that the IT Portuguese industry is strong on its processes and has a good level of maturity in project management.

Abstract
In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the MatSrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Abstract
A virtual enterprise (VE) is a temporary organisation that pools the core competencies of its member enterprises in order to exploit fast-changing market opportunities. Making successful collaborative partnerships is, in this context, a major challenge in today's competitive business environments. The success of such a 'virtual' organisation is strongly dependent on its composition, and the selection of partners becomes therefore a crucial issue. This problem is particularly difficult because of the uncertainties related to information, market dynamics, customer expectations and technology speed-up, with a strongly stochastic decision-making context. In this paper, a chance-constrained approach to rank alternative VE configurations in business environments with uncertainty, and vague and random information, is proposed. This approach is based on a two-stage model: a chance-constraint multi-objective directional Tabu Search metaheuristic, complemented by a 2-tuple fuzzy linguistic representation model. Preliminary computational results clearly demonstrate the potential of the approach for practical application.

Abstract
Kidney exchange programs (KEPs) allow the exchange of kidneys between incompatible donor-recipient pairs. Optimization approaches can help KEPs in defining which transplants should be made among all incompatible pairs according to some objective. The most common objective is to maximize the number of transplants. In this paper, we propose an integer programming model which addresses the objective of maximizing the expected number of transplants, given that there are equal probabilities of failure associated with vertices and arcs. The model is compact, i.e. has a polynomial number of decision variables and constraints, and therefore can be solved directly by a general purpose integer programming solver (e.g. Cplex).