Abstract
This paper describes an application of data envelopment analysis (DEA) to the performance assessment of Portuguese bank branches. The analysis shows how DEA can complement the profitability measure currently used at the bank. The use of an efficiency-profitability matrix enabled the characterisation of the branches' performance profile. Consistent with the bank's development objectives, the analysis focused on the relation between branch size and performance. Two alternative target setting strategies were explored. One eliminates pure technical inefficiencies by focusing on the selection of appropriate benchmarks. The other attains the branches' most productive scale size through the elimination of scale inefficiencies, with minimal changes to branches' scale size.

Abstract
The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed.The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed.

Abstract
The risk of the duration of a project exceeding a certain limit has been studied since the early papers proposing the PERT method but no results are available relating the statistical distribution of the total duration with the morphological features of the network. In this paper, a set of indicators is proposed to describe the morphology of the project network and an experimental research is carried out to relate the distribution of the total duration with such indicators. A random generator of project networks is used as well as a model to produce graphical representations of the network. Major results are presented showing how sensitive are the parameters of the distribution of the total duration to the morphology of the network, allowing the project manager to estimate the risk of delay in terms of the proposed indicators. Thus, these results can be used as a decision aid to select alternative designs for the project network taking into account the correspondent risk of delay.

Abstract
Standard versions of the maximum principle for optimal control problems with pathwise state inequality constraints are satisfied by a trivial set of multipliers in the case when the left endpoint is fixed and lies in the boundary of the state constraint set, and so give no useful information about optimal controls. Recent papers have addressed the problem of overcoming this degenerate feature of the necessary conditions. In these papers it is typically shown that, if a constraint qualification is imposed, requiring existence of inward pointing velocities, then sets of multipliers exist in addition to the trivial ones. A simple, new approach for deriving nondegenerate necessary conditions is presented, which permits relaxation of hypotheses previously imposed, concerning data regularity and convexity of the velocity set. (C) 1999 Academic Press.

Abstract

Abstract
The nesting problem consists of defining the cutting plan of a piece of raw material in smaller irregular shapes, and has applications in the apparel and footwear industries. Due to its NP-hard nature, the optimal solution can only be guaranteed by exhaustively trying all possible solutions and choosing the best one. Because this is impractical in real-life industrial problems, automatic approaches are based on optimization meta-heuristics that search for sub-optimal but good enough solutions. These optimization techniques rely on the construction and evaluation of several solutions, thus requiring heavy geometric manipulation of the irregular polygons that constitute the problem data. Efficient processing of this geometric information is thus necessary to make effective fully automatic approaches to nesting problems in industrial environments. This paper describes Fafner, an FPGA-based custom computing machine that is used to accelerate the geometric operations, that are in the core of heuristic solutions to the nesting problem. The system is used as an auxiliary processor attached to a low cost personal computer, and combines a custom programmable processor with an array of custom circuits for the processing of irregular polygons.