Abstract
The purpose of this paper is to present a methodology that allows higher education institutions (HEIs) to promote, to evaluate and to report on sustainability. The ultimate goal of the afore-mentioned methodology is to help HEIs achieve sustainability. First, a model entitled Sustainability in Higher Education Institutions (SusHEI) that generally describes and characterizes the functioning of an HEI was defined. SusHEI takes into account the core activities of any HEI (education and research), its impacts at economic, environmental and social levels, and the role of its community. SusHEI allowed for the establishment of internal dimensions interrelated to the functioning of an HEI. Then, a matricial representation of the model was developed. The matrix crosses internal dimensions (and eventually sub-dimensions) with sustainability dimensions (and eventually sub-dimensions) and it is quantified through indicators. There is a wide range of possible sustainability indicators that can be chosen, depending on the purpose and the public to whom the indicators/reports are addressed. The methodology is illustrated by a case-study - the Faculty of Engineering of the University of Porto (FEUP). This paper provides a methodology that enables the selection of sustainability indicators for sustainability reporting, assessment or even for benchmarking, and also eliminates some of the main weaknesses found in the models currently available. Higher Education Policy (2011) 24, 459-479. doi:10.1057/hep.2011.18

Abstract
We propose two exact algorithms for two-dimensional orthogonal packing problems whose main components are simple mixed-integer linear programming models. Based on the different forms of time representation in scheduling formulations, we extend the concept of multiple time grids into a second dimension and propose a hybrid discrete/continuous-space formulation. By relying on events to continuously locate the rectangles along the strip height, we aim to reduce the size of the resulting mathematical problem when compared to a pure discrete-space model, with hopes of achieving a better computational performance. Through the solution of a set of 29 test instances from the literature, we show that this was mostly accomplished, primarily because the associated search strategy can quickly find good feasible solutions prior to the optimum, which may be very important in real industrial environments. We also provide a comprehensive comparison to seven other conceptually different approaches that have solved the same strip packing problems.

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Abstract
Optimisation problems in Healthcare have received considerable attention for more than three decades. More recently, however, with decreasing birth rates in nearly all of the developed countries and increasing average longevity globally, optimisation issues in Healthcare have become noticeably important and attract keen interest from the Operations Research community. Over the years, attention has gradually expanded from resource allocation and strategic planning to include operational issues such as resource scheduling and treatment planning. This paper surveys several applications of Operations Research in the domain of Healthcare. In particular, the paper reviews key contributions addressing contemporary optimisation issues in this area. It highlights current research activities, focusing on a variety of optimisation problems as well as solution techniques used for solving the optimisation problems.

Abstract
One of the most important, applications of the Asymmetric Hamiltonian Path Problem is in scheduling. In this paper we describe a variant of this problem, and develop 1)011) a mathematical programming formulation and simple metaheuristics for solving it The formulation is based on a transformation of the input, data, in such a way that a standard mathematical programming model for the Asymmetric: Travelling Salesman Problem can be used on this slightly different problem. Two standard metaheuristics for the asymmetric travelling salesman are proposed and analysed on this variant: repeated random construction followed by local search with the 3-Exchange neighbourhood. and iterated local search based on the same neighbourhood and on a 4-Exchange perturbation. The computational results obtained show the interest, and the complementary merits of using a mixed-integer programming solver and an approximative method for the solution of this problem.

Abstract
Designers aspire to create engaging and desirable experiences. To that end they study users, aiming to better understand their preferences, ways of thinking and desired outcomes. In the service sector this task is more intricate as experiences encompass the whole customer journey, or the sequence of moments of interaction between customer and company. In services, one poorly designed interaction can severely compromise the overall experience. Despite experience holistic nature, current methods address its components separately, failing to provide an overall systematized picture. This paper presents Customer Experience Modeling, a novel multidisciplinary approach to systematize, represent and evaluate customer experiences to guide service and interaction design efforts. We illustrate this method with an application to a multimedia service provider built upon 17 interviews with service users.