Advanced global optimisation for mission analysis and design

This report describes the analysis and development of novel tools for the global optimisation of relevant mission design problems. A taxonomy was created for mission design problems, and an empirical analysis of their optimisational complexity performed - it was demonstrated that the use of global optimisation was necessary on most classes and informed the selection of appropriate global algorithms. The selected algorithms were then applied to the di®erent problem classes: Di®erential Evolution was found to be the most e±cient. Considering the speci¯c problem of multiple gravity assist trajectory design, a search space pruning algorithm was developed that displays both polynomial time and space complexity. Empirically, this was shown to typically achieve search space reductions of greater than six orders of magnitude, thus reducing signi¯cantly the complexity of the subsequent optimisation. The algorithm was fully implemented in a software package that allows simple visualisation of high-dimensional search spaces, and e®ective optimisation over the reduced search bounds.

Domestic energy models: complexities in defining specific tools

The domestic (residential) sector accounts for 30% of the world’s energy consumption hence plays a substantial role in energy management and CO2 emissions reduction efforts. Energy models have been generally developed to mitigate the impact of climate change and for the sustainable management and planning of energy resources. Although there are different models and model categories, they are generally categorised into top down and bottom up. Significantly, top down models are based on aggregated data while bottom up models are based on disaggregated data. These approaches create fundamental differences which have been the centre of debate since the 1970’s. These differences have led to noticeable discrepancies in results which have led to authors arguing that the models are of a more complementary than a substituting nature. As a result developing methods suggest that there is the need to integrate either the two models (bottom up − top down) or aspects that combine two bottom up models or an upgrade of top down models to compensate for the documented limitations. Diverse schools of thought argue in favour of these integrations – currently known as hybrid models. In this paper complexities of identifying country specific and/or generic domestic energy models and their applications in different countries have been critically reviewed. Predominantly from the review it is evident that most of these methods have been adapted and used in the ‘western world’ with practically no such applications in Africa.

PRESENTATION. Experimental and behavioral economics. Theory, tools and topics

This note presents the special issue on Experimental and Behavioral Economics. The volume includes some recent contributions from these correlated disciplines –empirical the former and theoretical the latter– and their potential contribution to the intersection of Economics with Psychology and Sociology. The project “El papel de la comparación social en las decisiones económicas bajo incertidumbre” (Junta de Andalucía, P07-SEJ-03155)” provided us with inspiration and financial support to publish this volume.

Bicorrelations and cross-bicorrelations as non-linearity tests and tools for exchange rate forecasting

This paper proposes and implements a new methodology for forecasting time series, based on bicorrelations and cross-bicorrelations. It is shown that the forecasting technique arises as a natural extension of, and as a complement to, existing univariate and multivariate non-linearity tests. The formulations are essentially modified autoregressive or vector autoregressive models respectively, which can be estimated using ordinary least squares. The techniques are applied to a set of high-frequency exchange rate returns, and their out-of-sample forecasting performance is compared to that of other time series models