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[EN] This article deals with the mean-variance optimisation frontier problem when realistic constraints are considered. Our proposed methodology hybridises a heuristic algorithm with an exact solution approach. A genetic algorithm is applied for the identification of the assets in the portfolio, whilst the asset weights in the portfolios are obtained by a quadratic programming model. The proposed algorithmic framework produces a constrained frontier that actually fulfils the bound and cardinality constraints, unlike other proposals where the frontier is composed of several subfrontiers, each one considering the cardinality constraint but with different assets in each sub-frontier, thus violating the cardinality constraint. This brings us to propose a surrogate similarity measure for the optimisation of the constrained frontier, which differs from a previous proposal where no bound constraints were considered.

[EN] University rankings assess the performance of universities in various fields and aggregate that performance into a single value. In this way, the aggregate performance of universities can be easily compared. The importance of rankings is evident, as they often guide the policy of Higher Education Institutions. The most prestigious multi-criteria rankings use indicators related to teaching and research. However, many stakeholders are now demanding a greater commitment to sustainable development from universities, and it is therefore necessary to include sustainability criteria in university rankings. The development of multi-criteria rankings is subject to numerous criticisms, including the subjectivity of the decision makers when assigning weights to the criteria. In this paper we propose a methodology based on goal programming that allows objective, transparent and reproducible weighting of the criteria. Moreover, it avoids the problems associated with the existence of correlated criteria. The methodology is applied to a sample of 718 universities, using 11 criteria obtained from two prestigious university rankings covering sustainability, teaching and research. A sensitivity analysis is carried out to assess the robustness of the results obtained. This analysis shows how the weights of the criteria and the universities' rank change depending on the lambda parameter of the goal programming model, which is the only parameter set by the decision maker.

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-030-85099-9_29., Frailty syndrome can be defined as a clinical state in which there is a rise in individual vulnerability, developing an increase in both the dependence of the person and mortality. Frailty is completely related to age. A fundamental factor to apply rehabilitative interventions successfully resides in having a simple and reliable method capable of identifying frailty syndrome. Frailty indexes (FI) have several sources of uncertainty trough the opinion of the patients, white coat effect and external factors. Moreover, in the clinical practice, the experience of the geriatricians led them to determine an approximation of the frailty level only with a simple handshake. Hand grip strength (HGS) has been widely used in tests by investigators and therapists to be able to diagnose sarcopenia and frailty, as it is a reliable indicator of the overall muscle strength, which decreases with age. Most researches focused mainly on peak HGS, which will not give insight on how the patient’s strength was distributed over time. In the present work it is proposed to evaluate HGS behavior over a period of time, and to develop a system based on Machine Learning for the identification of frailty levels using physiological features, FI and the classical signal processing based on statistics of the HGS signals. The starting hypothesis is that it can be identified the “way” of performing HGS correlated with the level of frailty. To achieve this goal a clinical study was designed and carried out with a cohort of 70 elderly persons, in two Hospitals., This work was partially supported by the Spanish Ministry of Ciencia, Innovación y Universidades under project RTI2018-096701-B-C22, and by the Catalonia FEDER program, resolution GAH/815/2018 under the project, PECT Garraf : Envelliment actiu i saludable i dependència., Peer Reviewed, Postprint (author's final draft)

[EN] The environmental, social, and governance (ESG) rating of firms is a useful tool for stakeholders and investment decision-makers. This paper develops a rough set model to relate ESG scores to popular corporate financial performance measures. This methodology permits handling with information in an uncertain, ambiguous, and imperfect context. A large database was gathered, including ESG scores, as well as industry sector and financial variables for publicly traded European companies during the period 2013-2018. We carried out 500 simulations of the rough set model for different values in the discretization parameter and different grouping scenarios of firms regarding ESG scores. The results suggest that the variables considered are useful in the prediction of ESG rank when firms are clustered in three or four equally balanced groups. However, the prediction power vanishes when a larger number of groups is computed. This would suggest that industry sector and financial variables serve to find big differences across firms regarding ESG, but the significance of the model drops when small differences in ESG performance are scrutinized.

[EN] Environmental valuation refers to a variety of techniques to assign monetary values to environmental impacts, especially non-market impacts. It has experienced a steady growth in the number of publications on the subject in the last 30 years. We performed a search for papers containing the term "environmental valuation" in the title, abstract, or keywords. The search was conducted with an online literature search engine of the Web of Science (WoS) electronic databases. A search of this database revealed that the term "environmental valuation" appeared for the first time in 1987. Since then a large number of studies have been published, including significant breakthroughs in theory and applications. In the present work 661 publications were selected for a review of the literature on environmental valuation over the period 1987-2019. This paper analyzes the evolution of the leading methodologies and authors, highlights the preference for the choice experiment method over the contingent valuation method, and shows that relatively few papers have had a strong impact on the researchers in this area

[EN] The aim of this study is to devise a sector restructuring model in which all the decision making units (DMUs) satisfy a predefined global efficiency level. The proposal makes several realistic assumptions regarding the merging of DMUs under specific circumstances. The model computes the global efficiency target by giving preference to merging DMUs over saving inputs, hence considering that the affected stakeholders may be resistant to restructuring, and this resistance may have overall negative effects on the image and reputation of the companies and organizations. In addition, the number of constituents in the new entities can be limited by the decision maker after the restructuring process, so that the model also considers a constraint on cardinality. The proposal combines the inverse data envelopment analysis (InvDEA), which computes the merger's input savings, and the genetic algorithm (GA), which solves the combinatorial problem of identifying the merging units. The proposal is illustrated by two examples from banking and higher education. (C) 2020 Elsevier Ltd. All rights reserved.

[EN] The present research proposes a novel methodology to solve the problems faced by investors who take into consideration different investment criteria in a fuzzy context. The approach extends the stochastic mean-variance model to a fuzzy multiobjective model where liquidity is considered to quantify portfolio's performance, apart from the usual metrics like return and risk. The uncertainty of the future returns and the future liquidity of the potential assets are modelled employing trapezoidal fuzzy numbers. The decision process of the proposed approach considers that portfolio selection is a multidimensional issue and also some realistic constraints applied by investors. Particularly, this approach optimizes the expected return, the risk and the expected liquidity of the portfolio, considering bound constraints and cardinality restrictions. As a result, an optimization problem for the constraint portfolio appears, which is solved by means of the NSGA-II algorithm. This study defines the credibilistic Sortino ratio and the credibilistic STARR ratio for selecting the optimal portfolio. An empirical study on the S&P100 index is included to show the performance of the model in practical applications. The results obtained demonstrate that the novel approach can beat the index in terms of return and risk in the analyzed period, from 2008 until 2018.

[EN] This paper extends the stochastic mean-semivariance model to a fuzzy multiobjective model, where apart from return and risk, also liquidity is considered to measure the performance of a portfolio. Uncertainty of future return and liquidity of each asset are modeled using L-R type fuzzy numbers that belong to the power reference function family. The decision process of this novel approach takes into account not only the multidimensional nature of the portfolio selection problem but also realistic constraints by investors. Particularly, it optimizes the expected return, the semivariance and the expected liquidity of a given portfolio, considering cardinality constraint and upper and lower bound constraints. The constrained portfolio optimization problem resulting is solved using the algorithm NSGA-II. As a novelty, in order to select the optimal portfolio, this study defines the credibilistic Sortino ratio as the ratio between the credibilistic risk premium and the credibilistic semivariance. An empirical study is included to show the effectiveness and efficiency of the model in practical applications using a data set of assets from the Latin American Integrated Market.