Abstract
In this paper we present a Benders decomposition approach for the Berth Allocation Problem (BAP). Benders decomposition is a cutting plane method that has been widely used for solving large-scale mixed integer linear optimization problems. On the other hand, the Berth Allocation Problem is a NP-hard and large-scale problem that has been gaining relevance both from the practical and scientific points of view. In this work we address the discrete and dynamic version of the problem, and develop a new decomposition approach and apply it to a reformulation of the BAP based on the Heterogeneous Vehicle Routing Problem with Time Windows (HVRPTW) model. In a discrete and dynamic BAP each berth can moor one vessel at a time, and the vessels are not all available to moor at the beginning of the planning horizon (there is an availability time window). Computational tests are run to compare the proposed Benders Decomposition with a state-of-the-art commercial solver. © 2019, Springer Nature Switzerland AG.

Abstract
The search for logistics best-practices in international trade has led to the appearance of the Berth Allocation Problem. If the vessels have release dates, the problem is proved to be NP-hard and the performance of exact algorithms is not satisfactory, leading to the use of metaheuristics. This paper develops a Hybrid Evolutionary Algorithm for the discrete and dynamic Berth Allocation Problem. A challenge of using Genetic Algorithms is the identification of the best approach to model a specific problem. This paper proposes the use of frontier techniques (Data Envelopment Analysis and Free Disposal Hull models) to compare the performances of alternative specifications of the parameters for the algorithm proposed and to identify efficient solutions.

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The performance of secondary schools is usually assessed based on students' results on national exams at the end of secondary education. This research uses data on academic achievements by first-year university students to benchmark secondary schools on their ability to lead students to success in higher education. The analysis is conducted using data of University of Porto and Catholic University of Porto, Portugal, for a three-year period, corresponding to more than 10.000 students from 65 degrees, for which the school of origin is known. A number of variables representing students' success in Higher education were constructed for each school in our sample and aggregated through a Benefit of the Doubt indicator. Results suggest that the schools' ranking based on schools' ability to prepare students for university success is quite different from the ranking based on results on national exams. Given these findings, we propose complementing schools' performance assessments (traditionally based on national exam results or indicators of value added) with indicators that account for the preparation of students for success in future challenges, which is indisputably a key objective of secondary education. We propose a composite indicator for the analysis of these complementary aims as well, and results show that frontier units indeed exhibit trade offs between traditional measures of performance and our new measure of performance.

Abstract
In recent decades, the concept of urban metabolism has been widely applied at different scales. This paper proposes an optimization model, based on Data Envelopment Analysis, for the evaluation and benchmarking of countries' metabolism. The EU-28 countries are analyzed based on economic and environmental indicators, including the resources consumed (energy and materials) and environmental pressures (GHG emissions and waste) associated with the value-added from the economic activities. The empirical results produced a ranking of countries' based on their metabolic performance underlying the creation of wealth, along with the targets for the countries with lower metabolic performance. This new metabolic approach is a contribution to the design of policies for the promotion of sustainable and resilient services.

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This paper investigates the relationship between students' performance and the type of school attended during upper secondary education. The performance of three different types of schools (Liceo, Technical and Professional schools) in four Italian macroregions (North West, North East, Centre, South & Islands) is investigated. A benchmarking analysis of the variability in students' performance among regions (within macroregions) for cohorts of students attending Liceo is also conducted. The data was collected at the student level from the Italian Institute for the Evaluation of Education System (INVALSI), for the academic year 2017/18. Families with higher socio-economic status may self-select into Liceo, so a direct comparison with vocational schools could lead to biased conclusions regarding the impact of school type on student performance. To overcome this limitation, we used a Propensity Score Matching approach prior to the estimation of efficiency. A pseudo-Malmquist index, based on a metafrontier and satisfying the circular property, is developed. It enables comparing the location of the best-practice frontier for each type of school and the spread in the educational efficiency of the students attending each type of school. Thus, best performance of a given school type corresponds to the combined effect of these two aspects. This study is an interesting starting point to challenge the stereotypes that persist in Italy, especially concerning general and vocational studies and geographic differences in educational achievements.

Abstract