Abstract
The scarcity of federal resources allocated to the Ministry of Defense causes the need for Brazilian Armed Forces to implement strategies that may allow achieving "more with less". For the Navy of Brazil, this strategy includes the need to improve and implement risk management tools and techniques in large defense projects. In this sense, the present study aims at contributing to this process through the design and validation of a synthetic risk model for military shipbuilding, containing the main risk events, causes and associated effects that may affect the success of these projects, in terms of costs and deadlines. This model will help in the prediction and control of these variables and their possible effects, enabling the anticipation of responses and the reduction of uncertainty. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
This paper describes the process of formulation and validation of a synthetic risk network model for the Brazilian military shipbuilding industry. This model is composed of risk events and their potential causes that will be the basis of the process of identification and analysis of future risks on similar projects. This process involved an extensive literature review to collect and list an initial catalogue of risks, causes and related effects, followed by an analysis to summarise and schematically group the risks. Then, the Delphi method with a panel of experts from the Brazilian Navy was used to analyse and assess the proposed model.

Abstract
This paper addresses the problem of maximising the expected number of transplants in kidney exchange programmes. New schemes for matching rearrangement in case of failure are presented, along with a new tree search algorithm used for the computation of optimal expected values. Extensive computational experiments demonstrate the effectiveness of the algorithm and reveal a clear superiority of a newly proposed scheme, subset-recourse, as compared to previously known approaches.

Abstract
In this paper we address the problem of maximizing the expected number of transplants in a kidney exchange program. We propose an integer programming model with an exponential number of decision variables which are associated with cycles. By introducing the concept of type of cycle, we avoid the complete cycle enumeration and develop a branch-and-price approach. © 2016 Elsevier B.V.

Abstract
In this paper we present a hybrid approach to integrative clustering based on the p-median problem with clients' preferences. We formulate the problem of simultaneous clustering of a set of objects, characterized by two sets of features, as a bi-level p-median model. An exact approach involving a branch-and-cut method combined with the simulated annealing algorithm is used, that allows one to find a two-source clustering. The proposed approach is compared with some well-known mathematical optimisation based clustering techniques applied to the NCI-60 tumour cell line anticancer drug screen dataset. The results obtained demonstrate the applicability of our approach to find competitive integrative clusterings. Copyright © by the paper's authors.

Abstract
Increasing demand for containerization compels container terminals to improve their performance. Uncoordinated scheduling of operations is one of the main factors accounting for poor performance at automated container terminals (ACTs). To increase land utilization efficiency and lower operational times, a new storage system called the split-platform automated storage/retrieval system (SP-AS/RS) has been introduced for temporary storage of containers. This paper describes a multi-objective mixed-integer programming (MIP) model that is based on a combination of multiple interacting sub-tasks. It is aimed at optimizing the integrated scheduling of handling and storage operations in ACTs. The MIP model objective function is to minimize delays in the loading/unloading tasks of the cranes and the travel time of vehicles and platforms in the SP-AS/RS. At the same time, a simulated annealing algorithm (SAA) that provides near-optimal solutions for the problem in a reasonable computation time is appraised. The results of this study show that the objective function of the MIP model is, on average, 58 % lower than that of the non-integrated scheduling method. On the other hand, the best objective function values obtained by the SAA indicate only a 3.7 % disadvantage in comparison with optimal values determined by the MIP model, demonstrating that the SAA is able to provide near-optimal solutions for the integrated scheduling of handling and storage operations. © 2015, World Maritime University.