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One of the fundamental economic problems is one of making the best use of limited resources. As a result, mathematical optimisation methods play a crucial role in economic theory. Covering the use of such methods in applied and policy contexts, this book deals not only with the main techniques (linear programming, nonlinear optimisation and dynamic programming), but also emphasizes the art of model-building and discusses fields such as optimisation over time

The main goal of simulation optimisation problem-solving process is minimising overall resources (time, money, human and technical resources), while maximising the overall information (e.g. system behaviour, sensitivity, optimal solutions) obtained in the process. The present paper gives a broad overview of the field of interest and describes new, integrative approaches for simulation and optimisation problems, using the achievements of different scientific areas.

The report discusses the role of impact assessment and evaluation of governmental decisions. The main objective of report is to develop a statistical model for optimisation of the set of policy instruments. The Draft of Rural Development Plan is used as example in order to develop and test the statistical model for optimising the allocation and use of funds. The statistical model is developed like as a small software version for policy‐makers to evaluate critical decisions. The statistical decision making theory is used in seeking solutions to optimise the choice of governmental decisions. The functions of losses or gains are defined on the basis of statistical data in two levels ‐ macroeconomic level and microeconomic level. In the statistical model the principles of the subjective probability are also applied in the case of unreliable and unavailable information. First Published Online: 14 Oct 2010

The report discusses the role of impact assessment and evaluation of governmental decisions. The main objective of report is to develop a statistical model for optimisation of the set of policy instruments. The Draft of Rural Development Plan is used as example in order to develop and test the statistical model for optimising the allocation and use of funds. The statistical model is developed like as a small software version for policy‐makers to evaluate critical decisions. The statistical decision making theory is used in seeking solutions to optimise the choice of governmental decisions. The functions of losses or gains are defined on the basis of statistical data in two levels ‐ macroeconomic level and microeconomic level. In the statistical model the principles of the subjective probability are also applied in the case of unreliable and unavailable information. First Published Online: 14 Oct 2010

PurposeThe purpose of this paper is to develop a more robust methodology for asset allocation for the property investment market which takes into account inherent valuation and data issues.Design/methodology/approachThe methodology applied is that of a bootstrap, borrowed from Carlstein, and is applied to an investment universe consisting of UK equities, gilts and property. The bootstrap selectively re‐samples the return time series by maintaining the economic cycle. The resulting return series is then used in the standard mean‐variance optimisation (MVO) on an unconstrained basis. Finally, a "sanity" test is applied on the correlation matrix to ensure that spurious instances do not skew the results.FindingsThe bootstrapped optimisation provides a range within which the portfolio weights can be manoeuvred instead of a static point under the standard MVO. It provides a more robust methodology for asset allocation and without giving any undue significance to one year of extreme result.Research limitations/implicationsThe current analysis is based on unconstrained portfolio optimisation, with a very limited investment universe. Additionally, by conforming with the MVO methodology, normality of asset returns is implicitly assumed, which is clearly not the case in the data used. Future work will also focus on an all‐property portfolio.Practical implicationsThe proposed methodology will prove to be useful for making asset allocation decisions, particularly in turbulent financial markets.Originality/valueThe paper focuses solely on bootstrapping with the IPD UK annual index and is particularly significant after one year of extremely poor performance of UK property. The results will be of use to fund managers and portfolio analysts.

In estimating the inputs into the modern portfolio theory (MPT) portfolio optimisation problem, it is usual to use equal weighted historic data. Equal weighting of the data, however, does not take account of the current state of the market. Consequently this approach is unlikely to perform well in any subsequent period as the data is still reflecting market conditions that are no longer valid. The need for some return weighting scheme that gives greater weight to the most recent data would seem desirable. Therefore, this study uses returns data which are weighted to give greater weight to the most recent observations to see if such a weighting scheme can offer improved ex ante performance over that based on unweighted data.

This is a conference paper and appears here with the permission of the publisher. ; Optimisation of structures requires the minimisation of an objective function subject to a set of constraints. Typically the objective function is mass for mass sensitive structures or cost for heavy engineering projects. However environmental sensitivity can be incorporated without any difficulty. For example in an energy scarce environment energy inputs can be considered as the objective function which can take into account all energy inputs such as material manufacture and structural element forming. Mass and energy are in fact more important considerations than cost. The barrier to this has been shaped by the political world where cost considerations are considered to be of paramount importance.

Arranging production activities to fit in with other construction activities is one of the basic ideas of the Just-in-Time approach. In the construction industry it has never been very fully applied. This is a mistake [1]. Construction works, particularly expensive parts of them, are a field where the approach can be and should be applied.

This research was financially supported by CRIDA, who also provided us data for this research. This master thesis has been supported partially by solution PJ09-W2.44 which has received funding from the SESAR Joint Undertaking (JU) under grant agreement No 874463. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the SESAR JU members other than the Union. Special thanks to EUROCONTROL and ENAIRE for providing essential data and insights. This thesis was also partially supported by Instituto de Matemáticas de Sevilla with an introductory research scholarship. The supervision of E. Carrizosa has been financed in part by research projects EC H2020 MSCA RISE NeEDS (Grant agreement ID: 822214); PID2019-110886RB-I00 (Ministerio de Ciencia e Innovación), FQM-329 and P18-FR-2369 (Junta de Andaluca, Spain) ; Quiero agradecer especialmente al Dr. Emilio Carrizosa su inestimable apoyo y que por creer en mi capacidad me haya iniciado en el maravilloso mundo de la investigación matemática. Quiero agradecer también al Dr. Alfonso Valenzuela su gran apoyo, ayuda y, lo más valioso, su tiempo. Y por último, a D. Antonio Ferrera le agradezco su incalculable ayuda y su magisterio sobre la organización del espacio aéreo. ; Universidad de Sevilla. Máster Universitario en Matemáticas

Les activités militaires altèrent la durée et la qualité du sommeil, pourtant essentiel à la santé et au maintien des performances mentales et physiques. Dans le contexte de la haute intensité, la gestion et l'optimisation du sommeil sont un enjeu opérationnel majeur pour maintenir dans la durée les performances des combattants et protéger leur état de santé. Les armées ont fait le choix de méthodes non pharmacologiques de gestion et d'optimisation du sommeil, dont l'efficacité a été démontrée dans des études de laboratoire et de terrain. L'optimisation du sommeil et de la récupération est un domaine de recherche et d'innovations avec des opportunités majeures offertes par le développement des objets connectés et de nouveaux outils d'analyses.