Abstract
In this paper we present a new constructive algorithm for nesting problems. The layout is built by successively adding a new piece to a partial solution, i.e. to the set of pieces previously nested. Several criteria to choose the next piece Co place and its orientation are proposed and tested. Different objective functions are also proposed to evaluate and compare partial solutions. A total of 126 variants of the algorithm, generated by the complete set of combinations of criteria and objective functions, are computationally tested. The computational experiments are based on data sets published in the literature or provided by other authors. In some cases this new algorithm generates better solutions than the best known (published) solutions.

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.

Abstract
In this paper we deal with the optimisation problem involved in determining the maximal margin separation hyperplane in support vector machines. We consider three different formulations, based on L-2 norm distance (the standard case), L-1 norm, and L-infinity norm. We consider separation in the original space of the data (i.e., there are no kernel transformations). For any of these cases, we focus on the following problem: having the optimal solution for a given training data set, one is given a new training example. The purpose is to use the information about the solution of the problem without the additional example in order to speed up the new optimisation problem. We also consider the case of reoptimisation after removing an example from the data set. We report results obtained for some standard benchmark problems.

Abstract
The UML is recognized to be the dominant diagrammatic modeling language in the software industry. However, it's support for building interactive systems is still acknowledged to be insufficient. There is a common misconception that the same models developed to support the design of the application internals are also adequate to support interaction design, leveraging the usability aspects of the applications. In this paper we identify and discuss the major problems using the UML to document, specify and design interactive systems. Here we propose a UML profile for interactive systems development that leverages oil human-computer interaction domain knowledge under the common notation and semantics of the UML. Our proposal integrates with existing object-oriented software engineering best practice, fostering co-evolutionary development of interactive systems and enabling artifact change between software engineering and human-computer interaction.

Abstract
Wisdom is a new software engineering method addressing the specific needs of small reams that develop and maintain interactive systems. Because Wisdom defines a process, notation, and project philosophy, it can smoothly be applied in small companies leveraging on their communication, speed, and flexibility.

Abstract
We propose a data mining model that captures the user navigation behaviour patterns. The user navigation sessions are modelled as a hypertext probabilistic grammar whose higher probability strings correspond to the user's preferred trails. An algorithm to efficiently mine such trails is given. We make use of the N gram model which assumes that the last N pages browsed affect the probability of the next page to be visited. The model is based on the theory of probabilistic grammars providing it with a sound theoretical foundation for future enhancements. Moreover, we propose the use of entropy as an estimator of the grammar's statistical properties. Extensive experiments were conducted and the results show that the algorithm runs in linear time, the grammar's entropy is a good estimator of the number of mined trails and the real data rules confirm the effectiveness of the model. © Springer-Verlag Berlin Heidelberg 2000.