Abstract
This study deals with industrial processes that produce soft drink bottles in different flavours and sizes, carried out in two synchronised production stages: liquid preparation and bottling. Four single-stage formulations are proposed to solve the synchronised two-stage lot sizing and scheduling problem in soft drink production synchronising the first stage's syrup lots in tanks with the second stage's soft drink lots on bottling lines. The first two formulations are variants of the General Lot Sizing and Scheduling Problem (GLSP) with sequence-dependent setup times and costs, while the other two are based on the Asymmetric Travelling Salesman Problem (ATSP) with different subtour elimination constraints. All models are computationally tested and compared to the original two-stage formulation introduced in Ferreira et al. (2009), using data based on a real-world bottling plant. The results show not only the superiority of the single-stage models if compared to the two-stage formulation, but also the much faster solution times of the ATSP-based models.

Abstract
This article describes a real-world production planning and scheduling problem occurring at an integrated pulp and paper mill (P&P) which manufactures paper for cardboard out of produced pulp. During the cooking of wood chips in the digester, two by-products are produced: the pulp itself (virgin fibers) and the waste stream known as black liquor. The former is then mixed with recycled fibers and processed in a paper machine. Here, due to significant sequence-dependent setups in paper type changeovers, sizing and sequencing of lots have to be made simultaneously in order to efficiently use capacity. The latter is converted into electrical energy using a set of evaporators, recovery boilers and counter-pressure turbines. The planning challenge is then to synchronize the material flow as it moves through the pulp and paper mills, and energy plant, maximizing customer demand (as backlogging is allowed), and minimizing operation costs. Due to the intensive capital feature of P&P, the output of the digester must be maximized. As the production bottleneck is not fixed, to tackle this problem we propose a new model that integrates the critical production units associated to the pulp and paper mills, and energy plant for the first time. Simple stochastic mixed integer programming based local search heuristics are developed to obtain good feasible solutions for the problem. The benefits of integrating the three stages are discussed. The proposed approaches are tested on real-world data. Our work may help P&P companies to increase their competitiveness and reactiveness in dealing with demand pattern oscillations.

Abstract
This paper presents a combination of optimization and data mining techniques to address the surgery scheduling problem. In this approach, we first develop a model to predict the duration of the surgeries using a data mining algorithm. The prediction model outcomes are then used by a mathematical optimization model to schedule surgeries in an optimal way. In this paper, we present the results of using three different data mining algorithms to predict the duration of surgeries and compare them with the estimates made by surgeons. The results obtained by the data mining models show an improvement in estimation accuracy of 36%.We also compare the schedules generated by the optimization model based on the estimates made by the prediction models against reality. Our approach enables an increase in the number of surgeries performed in the operating theater, thus allowing a reduction on the average waiting time for surgery and a reduction in the overtime and undertime per surgery performed. These results indicate that the proposed approach can help the hospital improve significantly the efficiency of resource usage and increase the service levels. © Springer-Verlag 2012.

Abstract
Rekindles can represent a high burden on wildland fire suppression resources, but despite the relevance of this phenomenon in Portugal, related research is still scarce. Seeking to contribute to address this gap, the purpose of this study was to organize and provide an overview of the problem of rekindles in Portugal, and to verify whether evidence exists that the high proportion of rekindles in Portugal is related to the double duty of Portuguese firefighters to perform initial attack and mop-up operations. Our study included informal meetings, formal recorded interviews, dispatch centre visits, actual rekindle observation, and an analysis of the National Forest Authority database. From the study of genealogies of rekindles, we concluded that 17.2% additional forest fires (rekindles in successive generations) had their origin in only 7.4% of primary fires. Through linear regression analysis, we found that their proportions increase in days with more occurrences, preliminarily supporting the hypothesis of premature abandonment of mop-up operations, as a result from the pressure to immediately attack starting fires by the same crews. A more detailed analysis of two representative districts highlighted specific organizational and natural challenges to successful mop-up efforts and provided further evidence of the hazardousness of rekindles. © 2012 WIT Press.

Abstract
This paper provides a review of the literature on applications of the Driving forces, Pressure, State, Impact, Response (DPSIR) framework to fisheries. The interpretation given to each DPSIR category differs in existing studies, and as a result the indicators used to support fisheries management also vary considerably. This impairs comparisons concerning the state of different fishery systems, and does not provide a common base of knowledge concerning potential management measures that can be adopted in a given context. This paper clarifies the interpretation of each DPSIR category and proposes a set of indicators that can be applied in fishery contexts. The set of indicators proposed is also classified according to sustainability dimensions. It is argued that organising the indicators according to the DPSIR framework and sustainability dimensions (ecologic, economic, social and governance) is a positive contribution to serve as a guideline for future applications to adopt standardized indicators and improve fisheries management.

Abstract
Schematic Maps are mainly used for depicting transportation networks. They are generated through a schematization process where irrelevant details are eliminated and important details are emphasized. This process, being manually performed by teams of expert designers, is expensive and time consuming. Such manual execution is unsuitable for the production of schematic maps for location-based services or on-demand schematic maps, as near real-time and user-centered properties are needed. This work proposes GeneX, a framework that can support the automated generation of schematic maps. The framework and a new algorithms developed were able to completely eliminate erroneous map point placement, and to decrease by 33% the contention for map point placement, producing schematic maps without human intervention in soft real time.