Abstract
A virtual enterprise (VE) is a temporary organisation that pools member enterprises core competencies and exploits fast changing market opportunities. VEs offer new opportunities to companies operating with a growing number of participants (consumers, vendors, partners and others) in a global business environment. The success of such an organisation is strongly dependent on its composition, and the selection of partners therefore becomes a crucial issue. Partner selection can be viewed as a multi-criteria decision making problem that involves assessing trade-offs between conflicting tangible and intangible criteria, and stating preferences based on incomplete or non-available information. In general, this is a very complex problem due to the large number of alternatives and criteria of different types (quantitative, qualitative and stochastic). In this paper we propose an integrated approach to rank alternative VE configurations using an extension of TOPSIS (a technique for ordering preferences by similarity to an ideal solution) for fuzzy data, improved through the use of a tabu search meta-heuristic. A sensitivity analysis is also presented. Preliminary computational results clearly demonstrate the potential of the approach for practical application.

Abstract
We propose a multiobjective local search metaheuristic for a mean-risk multistage capacity investment problem with irreversibility, lumpiness and economies of scale in capacity costs. Conditional value-at-risk is considered as a risk measure. Results of a computational study are presented and indicate that the approach is capable of producing high-quality approximations to the efficient sets with a modest computational effort. The best results are achieved with a new hybrid approach, combining Tabu Search and Variable Neighbourhood Search.

Abstract
In this paper we address two major challenges presented by stochastic discrete optimisation problems: the multiobjective nature of the problems, once risk aversion is incorporated, and the frequent difficulties in computing exactly, or even approximately, the objective function. The latter has often been handled with methods involving sample average approximation, where a random sample is generated so that population parameters may be estimated from sample statistics-usually the expected value is estimated from the sample average. We propose the use of multiobjective metaheuristics to deal with these difficulties, and apply a multiobjective local search metaheuristic to both exact and sample approximation versions of a mean-risk static stochastic knapsack problem. Variance and conditional value-at-risk are considered as risk measures. Results of a computational study are presented, that indicate the approach is capable of producing high-quality approximations to the efficient sets, with a modest computational effort.

Abstract
In today's changing environments, organizational design must take into account; the fact that business processes are incomplete by nature and that they should be managed in such a way that they do not restrain human intervention. In this paper we propose the embedding of social software features, such as collaboration and wiki-like features, in the modeling and execution tools of business processes. These features will foster people empowerment in the bottom-up design and execution of business processes. We conclude this paper by identifying some research issues about the implementation of the tool and its methodological impact on Business Process Management.

Abstract
The process of resources systems selection takes an important part in Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. However, the resources systems selection is still a difficult matter to solve in a D/A/VE, as it is pointed out in this paper. Globally, we can say that the selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project), we intend in this paper to show: a formulation of a kind of resources selection problem and the limitations of the algorithms proposed to solve it. We formulate a particular case of the problem as an integer programming, which is solved using simplex and branch and bound algorithms, and identify their performance limitations (in terms of processing time) based on simulation results. These limitations depend on the number of processing tasks and on the number of pre-selected resources per processing tasks, defining the domain of applicability of the algorithms for the problem studied. The limitations detected open the necessity of the application of other kind of algorithms (approximate solution algorithms) outside the domain of applicability founded for the algorithms simulated. However, for a broker tool it is very important the knowledge of algorithms limitations, in order to, based on problem features, develop and select the most suitable algorithm that guarantees a good performance

Abstract
Oliveira, M. M., Camanho, A. S., and Gaspar, M. B. 2010. Technical and economic efficiency analysis of the Portuguese artisanal dredge fleet. - ICES Journal of Marine Science, 67: 1811-1821. An efficiency analysis of the commercial dredge fleet operating along the south coast of Portugal between 2005 and 2007 sought to determine the efficiency of the vessels using data envelopment analysis models, considering fixed inputs (vessel power, length, tonnage, and an indicator of stock biomass) and a variable input (number of days at sea). The annual quota per vessel was also included in the model as a contextual factor. In the technical-efficiency (TE) analysis, outputs were defined by the catch weight for each of the three target species (bivalves). Using price data for each species in the wholesale market, revenue efficiency was also estimated to complement the TE analysis. The advantage of the approach lies in the ability to separate technical aspects from allocative aspects in the efficiency assessment, allowing two-dimensional graphic representation of vessel performance. The procedure allows the identification of benchmark vessels, which maximized the catch weight of the species landed, given their inputs, as well as the vessels that selected the appropriate target species to maximize the revenue of the fishing activity, given output prices. The approach also allowed the specification of targets for inefficient vessels that correspond to the catch by species, permitting revenue maximization from fishing.