Abstract
This paper presents a conceptual framework where the development of an information system for aggregate management of virtual / networked enterprises is taking place. Firstly, the general objectives of the system are described. An ontology based development approach is presented, assuming the role of conceptual guidance, both for the requirements analysis and design phases. Finally, a broad specification of aggregate management in this context is described through use cases.

Abstract
Partner selection in virtual enterprises (VE) can be viewed as a multi-criteria decision making problem that involves assessing trade-offs between conflicting tangible and intangible criteria. In general, this is a very complex problem due to the dynamic topology of the network, the large number of alternatives and the different types of criteria. In this paper we propose an exploratory process to help the decision-maker obtain knowledge about the network in order to identify the criteria and the companies that best suit the needs of each particular project. This process involves a multi-objective tabu search metaheuristic designed to find a good approximation of the Pareto front, and a fuzzy TOPSIS algorithm to rank the alternative VE configurations. In the exploratory phase we apply clustering analysis to confine the search according to the decision-maker beliefs, and case base reasoning, an artificial intelligence approach, to totally or partially construct VEs by reusing past experiences. Preliminary computational results clearly demonstrate the potential of the approach for practical application.

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
This paper describes an application of genetic algorithms to the bus driver scheduling problem. The application of genetic algorithms extends the traditional approach of Set Covering/Set Partitioning formulations, allowing the simultaneous consideration of several complex criteria. The genetic algorithm is integrated in a DSS but can be used as a very interactive tool or a stand-alone application. It incorporates the user's knowledge in a quite natural way and produces solutions that are almost directly implemented by the transport companies in their operational planning processes. Computational results with airline and bus crew scheduling problems from real world companies are presented and discussed.

Abstract
Traditional Production Planning and Control systems do not successfully deal with new organisational forms of manufacturing, like production "islands", product oriented or customer driven production. These current trends lead in practice to a strong decentralisation of production management tasks and to an "object oriented structuring" of the manufacturing process. Planning and operation in this global environment requires new skills and new approaches, namely, the co-ordination of global networks of manufacturing units and of large complex supply chains. In this paper, we present a decentralised information system designed to address the tasks of production planning that result from sales orders, originated in customers located anywhere in the world, and accomplished through a distributed manufacturing network. The system addresses the requirements of a make-to-order environment and is hopefully able to produce realistic satisfactory delivery dates. The information infrastructure designed and implemented using distributed object-oriented technology with a component based architecture has proven to be efficient and powerful, satisfying all the major tight requirements of information systems in an environment of distributed manufacturing.

Abstract
Although single objective metaheuristics are widely spread and applied in many combinatorial optimisation problems, only very recently have multiobjective metaheuristics (MOMH) been designed and used in practice. They aim at obtaining good approximations of the set of nondominated solutions of a problem, in an efficient way. In this work, we have applied multiobjective versions of simulated annealing and taboo search to the resource constrained project scheduling problem (RCPSP), in order to minimise the makespan, the "weighted" lateness of activities and the violation of resource constraints. Computational experience performed on randomly generated instances shows that this general approach is flexible, effective and able to deal with multiple objectives and with variations in the problem structure.