Emerging M&S Application in Risk Management

There has been compelling signs of the great potential of building further synergy with academics, researchers, and industry practitioners from the areas of Modeling and Simulation (M&S) managing risk events. This paper provides an introduction to risk management and how M&S has permeated the risk management process. The trend has been to harness the advantages of M&S tools and techniques in terms of efficiency and effectiveness in managing risks. However, the more important contribution of M&S may be in how it provides a way for specialists in various disciplines or industries interact to manage risks that require multi-disciplinary approach. This becomes possible due to the capabilities of many M&S tools and techniques to be used to recognize the various objectives in risk management scenarios, as well as the need for multiple and non-commensurate performance parameters

Computing the Mean-Variance-Sustainability Nondominated Surface by ev-MOGA

[EN] Despite the widespread use of the classical bicriteria Markowitz mean-variance framework, a broad consensus is emerging on the need to include more criteria for complex portfolio selection problems. Sustainable investing, also called socially responsible investment, is becoming a mainstream investment practice. In recent years, some scholars have attempted to include sustainability as a third criterion to better reflect the individual preferences of those ethical or green investors who are willing to combine strong financial performance with social benefits. For this purpose, new computational methods for optimizing this complex multiobjective problem are needed. Multiobjective evolutionary algorithms (MOEAs) have been recently used for portfolio selection, thus extending the mean-variance methodology to obtain a mean-variance-sustainability nondominated surface. In this paper, we apply a recent multiobjective genetic algorithm based on the concept of epsilon-dominance called ev-MOGA. This algorithm tries to ensure convergence towards the Pareto set in a smart distributed manner with limited memory resources. It also adjusts the limits of the Pareto front dynamically and prevents solutions belonging to the ends of the front from being lost. Moreover, the individual preferences of socially responsible investors could be visualised using a novel tool, known as level diagrams, which helps investors better understand the range of values attainable and the tradeoff between return, risk, and sustainability.This work was funded by "Ministerio de Economia y Competitividad" (Spain), research project RTI2018-096904B-I00, and "Conselleria de Educacion, Cultura y DeporteGeneralitat Valenciana" (Spain), research project AICO/2019/055Garcia-Bernabeu, A.; Salcedo-Romero-De-Ávila, J.; Hilario Caballero, A.; Pla Santamaría, D.; Herrero Durá, JM. (2019). Computing the Mean-Variance-Sustainability Nondominated Surface by ev-MOGA. Complexity. 2019:1-12. https://doi.org/10.1155/2019/6095712S1122019Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77. doi:10.2307/2975974Hirschberger, M., Steuer, R. E., Utz, S., Wimmer, M., & Qi, Y. (2013). Computing the Nondominated Surface in Tri-Criterion Portfolio Selection. Operations Research, 61(1), 169-183. doi:10.1287/opre.1120.1140Utz, S., Wimmer, M., Hirschberger, M., & Steuer, R. E. (2014). Tri-criterion inverse portfolio optimization with application to socially responsible mutual funds. European Journal of Operational Research, 234(2), 491-498. doi:10.1016/j.ejor.2013.07.024Utz, S., Wimmer, M., & Steuer, R. E. (2015). Tri-criterion modeling for constructing more-sustainable mutual funds. European Journal of Operational Research, 246(1), 331-338. doi:10.1016/j.ejor.2015.04.035Qi, Y., Steuer, R. E., & Wimmer, M. (2015). An analytical derivation of the efficient surface in portfolio selection with three criteria. Annals of Operations Research, 251(1-2), 161-177. doi:10.1007/s10479-015-1900-yGasser, S. M., Rammerstorfer, M., & Weinmayer, K. (2017). Markowitz revisited: Social portfolio engineering. European Journal of Operational Research, 258(3), 1181-1190. doi:10.1016/j.ejor.2016.10.043Qi, Y. (2018). On outperforming social-screening-indexing by multiple-objective portfolio selection. Annals of Operations Research, 267(1-2), 493-513. doi:10.1007/s10479-018-2921-0Nathaphan, S., & Chunhachinda, P. (2010). Estimation Risk Modeling in Optimal Portfolio Selection: An Empirical Study from Emerging Markets. Economics Research International, 2010, 1-10. doi:10.1155/2010/340181DeMiguel, V., Garlappi, L., & Uppal, R. (2007). Optimal Versus Naive Diversification: How Inefficient is the 1/NPortfolio Strategy? Review of Financial Studies, 22(5), 1915-1953. doi:10.1093/rfs/hhm075Metaxiotis, K., & Liagkouras, K. (2012). Multiobjective Evolutionary Algorithms for Portfolio Management: A comprehensive literature review. Expert Systems with Applications, 39(14), 11685-11698. doi:10.1016/j.eswa.2012.04.053Bertsimas, D., & Shioda, R. (2007). Algorithm for cardinality-constrained quadratic optimization. Computational Optimization and Applications, 43(1), 1-22. doi:10.1007/s10589-007-9126-9Chang, T.-J., Yang, S.-C., & Chang, K.-J. (2009). Portfolio optimization problems in different risk measures using genetic algorithm. Expert Systems with Applications, 36(7), 10529-10537. doi:10.1016/j.eswa.2009.02.062Woodside-Oriakhi, M., Lucas, C., & Beasley, J. E. (2011). Heuristic algorithms for the cardinality constrained efficient frontier. European Journal of Operational Research, 213(3), 538-550. doi:10.1016/j.ejor.2011.03.030Chen, B., Lin, Y., Zeng, W., Xu, H., & Zhang, D. (2017). The mean-variance cardinality constrained portfolio optimization problem using a local search-based multi-objective evolutionary algorithm. Applied Intelligence, 47(2), 505-525. doi:10.1007/s10489-017-0898-zLiagkouras, K. (2019). A new three-dimensional encoding multiobjective evolutionary algorithm with application to the portfolio optimization problem. Knowledge-Based Systems, 163, 186-203. doi:10.1016/j.knosys.2018.08.025Kaucic, M., Moradi, M., & Mirzazadeh, M. (2019). Portfolio optimization by improved NSGA-II and SPEA 2 based on different risk measures. Financial Innovation, 5(1). doi:10.1186/s40854-019-0140-6Silva, Y. L. T. V., Herthel, A. B., & Subramanian, A. (2019). A multi-objective evolutionary algorithm for a class of mean-variance portfolio selection problems. Expert Systems with Applications, 133, 225-241. doi:10.1016/j.eswa.2019.05.018Anagnostopoulos, K. P., & Mamanis, G. (2009). Multiobjective evolutionary algorithms for complex portfolio optimization problems. Computational Management Science, 8(3), 259-279. doi:10.1007/s10287-009-0113-8Ehrgott, M., Klamroth, K., & Schwehm, C. (2004). An MCDM approach to portfolio optimization. European Journal of Operational Research, 155(3), 752-770. doi:10.1016/s0377-2217(02)00881-0Steuer, R. E., Qi, Y., & Hirschberger, M. (2006). Suitable-portfolio investors, nondominated frontier sensitivity, and the effect of multiple objectives on standard portfolio selection. Annals of Operations Research, 152(1), 297-317. doi:10.1007/s10479-006-0137-1Anagnostopoulos, K. P., & Mamanis, G. (2010). A portfolio optimization model with three objectives and discrete variables. Computers & Operations Research, 37(7), 1285-1297. doi:10.1016/j.cor.2009.09.009Hallerbach, W. (2004). A framework for managing a portfolio of socially responsible investments. European Journal of Operational Research, 153(2), 517-529. doi:10.1016/s0377-2217(03)00172-3Ballestero, E., Bravo, M., Pérez-Gladish, B., Arenas-Parra, M., & Plà-Santamaria, D. (2012). Socially Responsible Investment: A multicriteria approach to portfolio selection combining ethical and financial objectives. European Journal of Operational Research, 216(2), 487-494. doi:10.1016/j.ejor.2011.07.011Cabello, J. M., Ruiz, F., Pérez-Gladish, B., & Méndez-Rodríguez, P. (2014). Synthetic indicators of mutual funds’ environmental responsibility: An application of the Reference Point Method. European Journal of Operational Research, 236(1), 313-325. doi:10.1016/j.ejor.2013.11.031Calvo, C., Ivorra, C., & Liern, V. (2014). Fuzzy portfolio selection with non-financial goals: exploring the efficient frontier. Annals of Operations Research, 245(1-2), 31-46. doi:10.1007/s10479-014-1561-2Laumanns, M., Thiele, L., Deb, K., & Zitzler, E. (2002). Combining Convergence and Diversity in Evolutionary Multiobjective Optimization. Evolutionary Computation, 10(3), 263-282. doi:10.1162/106365602760234108Blasco, X., Herrero, J. M., Sanchis, J., & Martínez, M. (2008). A new graphical visualization of n-dimensional Pareto front for decision-making in multiobjective optimization. Information Sciences, 178(20), 3908-3924. doi:10.1016/j.ins.2008.06.01

A conceptual framework for crop-based agri-food supply chain characterization under uncertainty

[EN] Crop-based Agri-food Supply Chains (AFSCs) are complex systems that face multiple sources of uncertainty that can cause a significant imbalance between supply and demand in terms of product varieties, quantities, qualities, customer requirements, times and prices, all of which greatly complicate their management. Poor management of these sources of uncertainty in these AFSCs can have negative impact on quality, safety, and sustainability by reducing the logistic efficiency and increasing the waste. Therefore, it becomes crucial to develop models in order to deal with the key sources of uncertainty. For this purpose, it is necessary to precisely understand and define the problem under study. Even, the characterisation process of this domains is also a difficult and time-consuming task, especially when the right directions and standards are not in place. In this chapter, a Conceptual Framework is proposed that systematically collects those aspects that are relevant for an adequate crop-based AFSC management under uncertainty.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015Alemany Díaz, MDM.; Esteso, A.; Ortiz Bas, Á.; Hernández Hormazabal, JE.; Fernández, A.; Garrido, A.; Martin, J.... (2021). A conceptual framework for crop-based agri-food supply chain characterization under uncertainty. Studies in Systems, Decision and Control. 280:19-33. https://doi.org/10.1007/978-3-030-51047-3_2S1933280Taylor, D.H., Fearne, A.: Towards a framework for improvement in the management of demand in agri-food supply chains. 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"It's all up here": adaptation and improvisation within the modern project

This paper considers organisational improvisation, and in particular, adaptation as a specific component of improvisational work(Miner et al., 2001), and how it may assist in resolving or assisting with some of the challenges surrounding recent shifts in our understanding of project-based management. Examples focus on the use of adaptation to cope with ambiguity and uncertainty, caused by execution in problematic and turbulent organisational environments. The literature on improvisation suggests that adapting previously successful interventions reduces and manages the risk of improvising by engaging with the 'adaptation component of organisational improvisation. This practice assists in ensuring that the additional risk of completely novel activity is avoided. This paper explores adaptation within the project domain, and also unpicks the rhetoric from the reality of adaptation within projects, confirming its benefits, setting out the circumstances where experience informs the practice, and offering readily usable and applicable insights

Regulating nanotechnologies: risk, uncertainty and the global governance gap

This article builds on research for a two-year project on nanotechnology regulation in the US and Europe (2008–09), which was funded by the European Commission. We are grateful to our collaborators in this project, at the London School of Economics, Chatham House, Environmental Law Institute and Project on Emerging Nanotechnologies, and especially Linda Breggin, Jay Pendergrass and Read Porter. We also received helpful suggestions from three anonymous reviewers and would like to thank them for their advice. Any remaining errors are our own. Nanosciences and nanotechnologies are set to transform the global industrial landscape, but the debate on how to regulate environmental, health and safety risks is lagging behind technological innovation. Current regulatory efforts are primarily focused on the national and regional level, while the international dimensions of nanotechnology governance are still poorly understood and rarely feature on the international agenda. However, with the ongoing globalization of nanosciences and the rapid expansion of international trade in nanomaterials, demand for international coordination and harmonization of regulatory approaches is set to increase. Yet, uncertainty about nanotechnology risk poses a profound dilemma for regulators and policy-makers. Uncertainty both creates demand for and stands in the way of greater international cooperation and harmonization of regulatory approaches. This article reviews the emerging debate on nanotechnology risk and regulatory approaches, investigates the current state of international cooperation and outlines the critical contribution that a global governance approach can make to the safe development of nanotechnologie

Advanced Techniques for Assets Maintenance Management

16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 Bergamo, Italy, 11–13 June 2018. Edited by Marco Macchi, László Monostori, Roberto PintoThe aim of this paper is to remark the importance of new and advanced techniques supporting decision making in different business processes for maintenance and assets management, as well as the basic need of adopting a certain management framework with a clear processes map and the corresponding IT supporting systems. Framework processes and systems will be the key fundamental enablers for success and for continuous improvement. The suggested framework will help to define and improve business policies and work procedures for the assets operation and maintenance along their life cycle. The following sections present some achievements on this focus, proposing finally possible future lines for a research agenda within this field of assets management

Selection of maintenance, renewal and improvement projects in rail lines using the analytic network process

[EN] This paper addresses one of the most common problems that a railway infrastructure manager has to face: to prioritise a portfolio of maintenance, renewal and improvement (MR&I) projects in a railway network. This decision-making problem is complex due to the large number of MR&I projects in the portfolio and the different criteria to take into consideration, most of which are influenced and interrelated to each other. To address this problem, the use of the analytic network process (ANP) is proposed. The method is applied to a case study in which the Local Manager of the public company, who is responsible for the MR&I of Spanish Rail Lines, has to select the MR&I projects which have to be executed first. Based on the results, it becomes evident that, for this case study, the main factor of preference for a project is the location of application rather than the type of project. The main contributions of this work are: the deep analysis done to identify and weigh the decision criteria, how to assess the alternatives and provide a rigorous and systematic decision-making process, based on an exhaustive revision of the literature and expertiseThe translation of this paper was funded by the Universitat Politecnica de Valencia.Montesinos-Valera, J.; Aragonés-Beltrán, P.; Pastor-Ferrando, J. (2017). Selection of maintenance, renewal and improvement projects in rail lines using the analytic network process. Structure and Infrastructure Engineering. 13(11):1476-1496. https://doi.org/10.1080/15732479.2017.1294189S147614961311Abril, M., Barber, F., Ingolotti, L., Salido, M. A., Tormos, P., & Lova, A. (2008). An assessment of railway capacity. Transportation Research Part E: Logistics and Transportation Review, 44(5), 774-806. doi:10.1016/j.tre.2007.04.001Ahern, A., & Anandarajah, G. (2007). 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Decision Support Framework for Infrastructure Maintenance Investment Decision Making. Journal of Management in Engineering, 32(1), 04015030. doi:10.1061/(asce)me.1943-5479.0000372Arunraj, N. S., & Maiti, J. (2010). Risk-based maintenance policy selection using AHP and goal programming. Safety Science, 48(2), 238-247. doi:10.1016/j.ssci.2009.09.005Asensio, J., & Matas, A. (2008). Commuters’ valuation of travel time variability. Transportation Research Part E: Logistics and Transportation Review, 44(6), 1074-1085. doi:10.1016/j.tre.2007.12.002Bana e Costa, C. A., & Oliveira, R. C. (2002). Assigning priorities for maintenance, repair and refurbishment in managing a municipal housing stock. European Journal of Operational Research, 138(2), 380-391. doi:10.1016/s0377-2217(01)00253-3Bana e Costa, C. A., & Vansnick, J.-C. (2008). A critical analysis of the eigenvalue method used to derive priorities in AHP. European Journal of Operational Research, 187(3), 1422-1428. doi:10.1016/j.ejor.2006.09.022Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis. doi:10.1007/978-1-4615-1495-4Bouch, C. J., Roberts, C., & Amoore, J. (2010). Development of a common set of European high-level track maintenance cost categories. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 224(4), 327-335. doi:10.1243/09544097jrrt316Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukiàs, A., & Vincke, P. (2000). Evaluation and Decision Models. International Series in Operations Research & Management Science. doi:10.1007/978-1-4615-1593-7Evaluation and Decision Models with Multiple Criteria. (2006). International Series in Operations Research & Management Science. doi:10.1007/0-387-31099-1Brans, J. P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The Promethee method. 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Mesoscale mapping of sediment source hotspots for dam sediment management in data-sparse semi-arid catchments

Land degradation and water availability in semi-arid regions are interdependent challenges for management that are influenced by climatic and anthropogenic changes. Erosion and high sediment loads in rivers cause reservoir siltation and decrease storage capacity, which pose risk on water security for citizens, agriculture, and industry. In regions where resources for management are limited, identifying spatial-temporal variability of sediment sources is crucial to decrease siltation. Despite widespread availability of rigorous methods, approaches simplifying spatial and temporal variability of erosion are often inappropriately applied to very data sparse semi-arid regions. In this work, we review existing approaches for mapping erosional hotspots, and provide an example of spatial-temporal mapping approach in two case study regions. The barriers limiting data availability and their effects on erosion mapping methods, their validation, and resulting prioritization of leverage management areas are discussed.BMBF, 02WGR1421A-I, GROW - Verbundprojekt SaWaM: Saisonales Wasserressourcen-Management in Trockenregionen: Praxistransfer regionalisierter globaler Informationen, Teilprojekt 1DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

A theoretical model for the application of Web 2.0 in e-Government

Government organisations in many countries have started embracing modern technologies such as second generation web (Web 2.0) in an attempt to maximize on the benefits of these technologies as well as keeping up with the current trend. Nevertheless, the advancement and the adoption of these of technologies is in its initial stages in the public sector. Therefore, the research problem is that the literature surrounding the application of Web 2.0 is still highly tentative and exploratory. In particular, there is a lack of research exploring the application of Web 2.0 technologies in the context of local e-Government. This study aims to address this research problem by presenting a comprehensive decision-making tool to aid the effective application of Web 2.0 technologies amongst local government authorities (LGAs). In doing so, resulting in the development of a theoretical model that is underpinned by information systems evaluation criteria and impact factors of Web 2.0 from an internal organizational perspective. By addressing the research problem, this study will make a significant contribution to the normative literature by providing new insights of Web 2.0 technologies within the public sector. This will be of specific relevance to scholars, policy makers, LGAs and practitioners who are interested in the adoption of Web 2.0 technologies in an e-Government context. This paper presents the proposed theoretical model and is largely devoted to an explanation on the development of the model