Constraint handling strategies in Genetic Algorithms application to optimal batch plant design

Optimal batch plant design is a recurrent issue in Process Engineering, which can be formulated as a Mixed Integer Non-Linear Programming(MINLP) optimisation problem involving specific constraints, which can be, typically, the respect of a time horizon for the synthesis of various products. Genetic Algorithms constitute a common option for the solution of these problems, but their basic operating mode is not always wellsuited to any kind of constraint treatment: if those cannot be integrated in variable encoding or accounted for through adapted genetic operators, their handling turns to be a thorny issue. The point of this study is thus to test a few constraint handling techniques on a mid-size example in order to determine which one is the best fitted, in the framework of one particular problem formulation. The investigated methods are the elimination of infeasible individuals, the use of a penalty term added in the minimized criterion, the relaxation of the discrete variables upper bounds, dominancebased tournaments and, finally, a multiobjective strategy. The numerical computations, analysed in terms of result quality and of computational time, show the superiority of elimination technique for the former criterion only when the latter one does not become a bottleneck. Besides, when the problem complexity makes the random location of feasible space too difficult, a single tournament technique proves to be the most efficient one

Forecasting Cryptocurrency Value by Sentiment Analysis: An HPC-Oriented Survey of the State-of-the-Art in the Cloud Era

This chapter surveys the state-of-the-art in forecasting cryptocurrency value by Sentiment Analysis. Key compounding perspectives of current challenges are addressed, including blockchains, data collection, annotation, and filtering, and sentiment analysis metrics using data streams and cloud platforms. We have explored the domain based on this problem-solving metric perspective, i.e., as technical analysis, forecasting, and estimation using a standardized ledger-based technology. The envisioned tools based on forecasting are then suggested, i.e., ranking Initial Coin Offering (ICO) values for incoming cryptocurrencies, trading strategies employing the new Sentiment Analysis metrics, and risk aversion in cryptocurrencies trading through a multi-objective portfolio selection. Our perspective is rationalized on the perspective on elastic demand of computational resources for cloud infrastructures

Understanding visibility in Iron Age and Roman southern Spain with exponential random graph models for visibility networks

Long-term changes in visibility patterns between urban settlements are considered an important factor for understanding Iron Age II settlement locations in Southern Spain. From some settlements, the surrounding landscape and other settlements could be visually controlled, and some settlements are argued to be intervisible to allow for communication through visual signals. However, the study of how these visibility patterns changed in the subsequent Roman period in this region is largely ignored. In this paper, we argue that visibility might still have structured interactions between communities in Roman times and should not be dismissed out of hand merely because more and other data sources are available as compared to the Iron Age. However, the way in which it affected human behaviour might have been different in Roman times as compared to the Iron Age. We argue that simulating archaeologists’ hypotheses about the emergence of inter-settlement visibility is a promising way of understanding such differences. To do this, we use exponential random graph modelling (ERGM), a statistical network simulation modelling technique that allows us to simulate hypotheses about the emergence and long-term change of visibility networks. We combine this approach with an exploratory analysis of the observed visibility networks between identified urban settlements, which will reveal similarities and differences in the changing patterns of visibility networks through time. The results of the ERGMs are then compared with the changes in the observed network structure. We conclude that our knowledge of the changes from the Iron Age II to the Roman settlement pattern suggests only gradual changes in the role of visibility in structuring inter-settlement interactions, possibly followed by a disintegration of the visibility network after the Roman Early Imperial period