Abstract
Electricity power planning is a serious national task that encompasses not only forecasts but more importantly the evolution in short, medium and long term of each element that composes the assumptions, the constraints and/or the parameters of the planning model. Deterministic models can bring simplicity to the electricity power planning but do not consider the uncertainties and sources of risk of the electricity system. On the other hand, stochastic models tend to include the behavior of one or more uncertain parameters that are critical to obtain a robust solution, being however more detailed and lengthy than deteministic models. The aim of this work was to identify the major sources of risk and uncertainties facing electricity system, representing valuable input for the electricit planner task. From this study it can be observed that several different behaviours for each uncertain parameter can be found along a time horizon. Thus, it is concluded that reling on average lowers can represent a reductionist approach and in order to obtain more reliable scenarios for future electricity system, the statistical charcateristics of each parameter should be considered in the electricity power planning.

Abstract

Abstract
A Shopping Centre (SC) is a "shop open to the public", installed in a building, which include parking, several shops, technical, management, and shopping arcade. In the current economic climate, the maintenance of complex buildings, like shopping centres, is performed under a tight budget context, and is essentially based on systems conditions. A maintenance model, to be effective, requires that maintenance service performance, covering the different building systems and components, is measured. This paper presents a methodology to measure the performance of SCs maintenance management through two major performance indicators: the Building Performance Indicator (BPI); and the Maintenance Efficiency Indicator (MEI). The results of its implementation to seven shopping centres, in Portugal, show that the general condition of the facilities is good (overall BPI= 86,45%) but the low MEI values (<0,37) indicates that insufficient resources are allocated to maintenance activities and this can compromise the future condition of the facilities.

Abstract
This paper addresses the cutting stock/leftover problem (CSLP), which differs from the ordinary cutting stock problem (CSP) by retaining stock leftovers that can be cut in the future to meet new demands. Therefore, leftovers are not considered waste in the current period. A new mathematical model for the CSLP is presented to capture a well-used strategy in the practice of cutting, which consists of partially cutting the objects in stock, and keeping the leftovers to be cut in the next periods. Computational experiments were made for the one-dimensional case, although other dimensions can be considered straightforward.

Abstract
In this paper a constructive heuristic for solving the staff scheduling problem of a glass manufacture unit is proposed. Based on simple calculations and algorithms, the developed procedure assigns working shifts and days-off to teams of employees, ensuring the satisfaction of a mandatory sequence of working shifts and the balance of the workload between employees. The computational times for the experiments with the case study company, with three eight-hour working shifts and five teams of employees, fell consistently below 5 seconds for a set of different planning periods. Results are compared with the ones achieved with an optimization model (MIP), demonstrating the good performance of the heuristic, also in terms of the quality of the achieved solutions. The heuristic rarely fails to produce a feasible solution and whenever the solution is feasible then it is also optimal. When tackling problems with a large number of teams, the heuristic maintains the good performance while the MIP model is not able to find any solution within 16 hours of running time. Although it was designed for a particular problem of the glass industry, tests show that the heuristic is flexible enough to be applied to problems with different features, from other activity sectors, encouraging further extensions of this work.

Abstract
Cutting and packing problems have been extensively studied in the literature in recent decades, mainly due to their numerous real-world applications while at the same time exhibiting intrinsic computational complexity. However, a major limitation has been the lack of problem generators that can be widely and commonly used by all researchers in their computational experiments. In this paper, a problem generator for every type of two-dimensional rectangular cutting and packing problems is proposed. The problems are defined according to the recent typology for cutting and packing problems proposed by Wascher, Haussner, and Schumann (2007) and the relevant problem parameters are identified. The proposed problem generator can significantly contribute to the quality of the computational experiments run with cutting and packing problems and therefore will help improve the quality of the papers published in this field.