Abstract
This paper presents an overview of a visual and interactive warehouse simulator developed with Visual C++ for Windows95/NT operating system. This simulator have been designed under an object oriented programming approach and looks to the warehouse by an hierarchic decision level point of view, which allows an interesting separation of the responsibilities on the system. It is a modular approach where each entity is responsible for its own integrity and functionality, and where the decision rules are separated on three fundamental levels(1): element level, control level and management level. Nevertheless, the main interest of this paper is not to introduce any kind of code statements of the simulator, but instead to present the reader the structure of the more relevant elements and the way they were modelled. At the same time it will be shown some of the user interface facilities and also some references to studies made using this warehouse simulator.

Abstract
The nesting (or placement) problem is an NP-hard combinatorial problem with important industrial applications, e.g. in apparel or footwear industry. This paper describes a hardware infrastructure to accelerate the processing of the underlying geometric information. The system consists of an FPGA-based reconfigurable platform enhanced by an ASIC for the processing of irregular polygons. The paper discusses the need for such a platform, establishes the main design guidelines and describes the architecture and modes of operation of both the reconfigurable infrastructure and the dedicated IC.

Abstract
In this paper we describe a hybrid strategy for solving combinatorial optimisation problems, obtained by coupling a local search method to an evolutionary algorithm, and we provide an application to a particular variant of the vehicle routing problem. The local search method has been devised specifically for this class of problems. It is based on a composite neighbourhood, which is searched iteratively up to the point where no further improvements are made. The evolutionary structure is the niche search, an algorithm based on the evolution of several independent niches. Niches whose individuals' fitness is good remain, and the others tend to be replaced. The separation of the population into niches allows for a good compromise between intensive search (inside each niche) and diversification (through the separation between the niches). We also describe how we integrate specific problem knowledge into an evolutionary structure, in order to achieve a high performance optimisation algorithm. All the steps that we consider necessary are described in detail: finding an appropriate representation, determining what is a relevant neighbourhood, setting up a local search method and finally integrating; the local search into an evolutionary algorithm.

Abstract
An industrial application of proportional hazards model is presented in this paper. The authors show the possibility of using both condition or quality covariates. The associated problems to the measurements and control values are evaluated. Conclusions show good agreement between predicted and real results.

Abstract
In some formulations of the vehicle replacement problem, in particular those leading to repair limit type models, the alternative policies are evaluated and compared over a fixed planning horizon. Although it has been widely recognised that the optimal policies derived under these formulations depend critically on the length of the horizon, no method has been presented so far to set appropriately this parameter. In this paper. the authors describe a method which overcomes this shortcoming. Once the best policy has been derived from a given finite horizon with length H, such a policy is repeated indefinitely over time and an equivalent annual rent is computed. The parametrisation of H leads to the definition of an annual rent function with a sequence of nearly equidistant local minima. It is suggested that in practice the second local minimum of this function leads to an adequate choice of the parameter H. The method can be applied both to stochastic and deterministic cost modelling situations. The method was tested using both real data from large samples of different types of passenger vehicles and artificially generated data. (C) 1997 Elsevier Science B.V.

Abstract
In this paper we describe niche search, a genetic-based optimisation approach which is characterised by an evolutionary search on two layers: the individual layer (which is comparable to search described in other genetic algorithms), and the niche layer. Neither of these searches is directed: both individuals and niches evolve based on the selection of the fittest. The numerical results obtained by niche search are quite promising, as our implementation has successfully handled all the tests carried out. The computational performance is considerably better than that of other algorithms of the same family analysed in the literature.