Abstract
This research aims at tackling a real-world long-haul freight transportation problem where tractors are allowed to exchange semi-trailers through several transshipment points until a request reaches its destiny. The unique characteristics of the considered logistics network allow for providing long-haul services by means of short-haul jobs, drastically reducing empty truck journeys. A greater flexibility is achieved with faster responses. Furthermore, the planning goals as well as the nature of the considered trips led to the definition of a new problem, the long-haul freight transportation problem with multiple transshipment locations. A novel mathematical formulation is developed to ensure resource synchronization while including realistic features, which are commonly found separately in the literature. Considering the complexity and dimension of this routing and scheduling problem, a mathematical programming heuristic (matheuristic) is developed with the objective of obtaining good quality solutions in a reasonable amount of time, considering the logistics business context. We provide a comparison between the results obtained for 79 real-world instances. The developed solution method is now the basis of a decision support system of a Portuguese logistics operator (LO).

Abstract
With rising healthcare costs, using health personnel and resources efficiently and effectively is critical. International cross-country and simple worker-to-population ratio comparisons are frequently used for improving the efficiency of health systems, planning of health human resources and guiding policy changes. These comparisons are made between countries typically of the same continental region. However, if used imprudently, inconsistencies arising from frail comparisons of health systems may outweigh the positive benefits brought by new policy insights. In this work, we propose a different approach to international health system comparisons. We present a methodology to group similar countries in terms of mortality, morbidity, utilisation levels, and human and physical resources, which are all factors that influence health gains. Instead of constructing an absolute rank or comparing against the average, the method finds countries that share similar ground, upon which more reliable comparisons can then be conducted, including performance analysis. We apply this methodology using data from the World Health Organization's Health for All database, and we present some interesting empirical relationships between indicators that may provide new insights into how such information can be used to promote better healthcare planning and policy guidance.

Abstract
Large food retailers have to deal with a complex distribution network with multiple distribution centres, different temperature requirements, and a vast range of store formats. This project used an optimization-simulation approach to help food retailer Sonae MC make the best decisions regarding product-warehouse-outlet assignment, product delivery modes planning and fleet sizing.

Abstract
This paper addresses an integrated framework for deciding about the supplier selection in the processed food industry under uncertainty. The relevance of including tactical production and distribution planning in this procurement decision is assessed. The contribution of this paper is three-fold. Firstly, we propose a new two-stage stochastic mixed-integer programming model for the supplier selection in the process food industry that maximizes profit and minimizes risk of low customer service. Secondly, we reiterate the importance of considering main complexities of food supply chain management such as: perishability of both raw materials and final products; uncertainty at both downstream and upstream parameters; and age dependent demand. Thirdly, we develop a solution method based on a multi-cut Benders decomposition and generalized disjunctive programming. Results indicate that sourcing and branding actions vary significantly between using an integrated and a decoupled approach. The proposed multi-cut Benders decomposition algorithm improved the solutions of the larger instances of this problem when compared with a classical Benders decomposition algorithm and with the solution of the monolithic model.

Abstract
This paper introduces a mathematical model (together with a relaxed version) and solution approaches for the multi-facility glass container production planning (MF-GCPP) problem. The glass container industry covers the production of glass packaging (bottle and jars), where a glass paste is continuously distributed to a set of parallel molding machines that shape the finished products. Each facility has a set of furnaces where the glass paste is produced in order to meet the demand. Furthermore, final product transfers between facilities are allowed to face demand. The objectives include meeting demand, minimizing inventory investment and transportation costs, as well as maximizing the utilization of the production facilities. A novel mixed integer programming formulation is introduced for MF-GCPP and solution approaches applying heuristics and meta-heuristics based on mathematical programming are developed. A multi-population genetic algorithm defines for each individual the partitions of the search space to be optimized by the MIP solver. A variant of the fix-and-optimize improvement heuristic is also introduced. The computational tests are carried on instances generated from real-world data provided by a glass container company. The results show that the proposed methods return competitive results for smaller instances, comparing to an exact solver method. In larger instances, the proposed methods are able to return high quality solutions.

Abstract
Large forest fires are notorious for their environmental and socio-economic impacts and are assigned a disproportionately high percentage of the fire management budget. This study addresses extremely large fires (ELF, C2500 ha) in Portugal (2003-2013). We analysed the effect of fire-suppression force variation on ELF duration, size and growth rate, versus the effect of the concomitant fire environment (namely fuel and weather) conditions. ELF occurred in highly flammable landscapes and typically were impelled by extreme fire weather conditions. Allocation of suppression resources (normalized per unit of burned area or perimeter length) was disparate among fires, suggesting inadequate incident management. Fire-suppression effort did not affect time to containment modelled by survival analysis. Regression tree analysis indicated ELF spread to be negatively affected by higher fire-suppression resourcing, less severe fire weather, lower time to containment and higher presence of <9-year-old fuels, by decreasing order of importance; regional variability was relevant. Fire environment-to-fire suppression ratios of influence were 3: 1 for fire size and 1: 1 for fire growth rate, respectively, explaining 76 and 60 % of the existing variability. Results highlight the opportunistic nature of large-fire containment. To minimize the area burned by ELF, management and operational improvements leading to faster containment are recommended, rather than higher fire-suppression resourcing; more effective identification and exploration of containment opportunities are preferable to the accumulation of suppression resources.