Some Remarks about the Complexity of Epidemics Management

Recent outbreaks of Ebola, H1N1 and other infectious diseases have shown that the assumptions underlying the established theory of epidemics management are too idealistic. For an improvement of procedures and organizations involved in fighting epidemics, extended models of epidemics management are required. The necessary extensions consist in a representation of the management loop and the potential frictions influencing the loop. The effects of the non-deterministic frictions can be taken into account by including the measures of robustness and risk in the assessment of management options. Thus, besides of the increased structural complexity resulting from the model extensions, the computational complexity of the task of epidemics management - interpreted as an optimization problem - is increased as well. This is a serious obstacle for analyzing the model and may require an additional pre-processing enabling a simplification of the analysis process. The paper closes with an outlook discussing some forthcoming problems

Optimal greenhouse cultivation control: survey and perspectives

Abstract: A survey is presented of the literature on greenhouse climate control, positioning the various solutions and paradigms in the framework of optimal control. A separation of timescales allows the separation of the economic optimal control problem of greenhouse cultivation into an off-line problem at the tactical level, and an on-line problem at the operational level. This paradigm is used to classify the literature into three categories: focus on operational control, focus on the tactical level, and truly integrated control. Integrated optimal control warrants the best economical result, and provides a systematic way to design control systems for the innovative greenhouses of the future. Research issues and perspectives are listed as well

Current Trends in Simheuristics: from smart transportation to agent-based simheuristics

Simheuristics extend metaheuristics by adding a simulation layer that allows the optimization component to deal efficiently with scenarios under uncertainty. This presentation reviews both initial as well as recent applications of simheuristics, mainly in the area of logistics and transportation. We also discuss a novel agent-based simheuristic (ABSH) approach that combines simheuristic and multi-agent systems to efficiently solve stochastic combinatorial optimization problems. The presentation is based on papers [1], [2], and [3], which have been already accepted in the prestigious Winter Simulation Conference.Peer ReviewedPostprint (published version

Decision support system for the long-term city metabolism planning problem

A Decision Support System (DSS) tool for the assessment of intervention strategies (Alternatives) in an Urban Water System (UWS) with an integral simulation model called “WaterMet²” is presented. The DSS permits the user to identify one or more optimal Alternatives over a fixed long-term planning horizon using performance metrics mapped to the TRUST sustainability criteria (Alegre et al., 2012). The DSS exposes lists of in-built intervention options and system performance metrics for the user to compose new Alternatives. The quantitative metrics are calculated by the WaterMet² model and further qualitative or user-defined metrics may be specified by the user or by external tools feeding into the DSS. A Multi-Criteria Decision Analysis (MCDA) approach is employed within the DSS to compare the defined Alternatives and to rank them with respect to a pre-specified weighting scheme for different Scenarios. Two rich, interactive Graphical User Interfaces, one desktop and one web-based, are employed to assist with guiding the end user through the stages of defining the problem, evaluating and ranking Alternatives. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple Scenarios. The efficacy of the DSS is demonstrated on a northern European case study inspired by a real-life urban water system for a mixture of quantitative and qualitative criteria. The results demonstrate how the DSS, integrated with an UWS modelling approach, can be used to assist planners in meeting their long-term, strategic level sustainability objectives

Digitalization in Thermodynamics

Digitalization is about data and how they are used. This has always been a key topic in applied thermodynamics. In the present work, the influence of the current wave of digitalization on thermodynamics is analyzed. Thermodynamic modeling and simulation is changing as large amounts of data of different nature and quality become easily available. The power and complexity of thermodynamic models and simulation techniques is rapidly increasing, and new routes become viable to link them to the data. Machine learning opens new perspectives, when it is suitably combined with classical thermodynamic theory. Illustrated by examples, different aspects of digitalization in thermodynamics are discussed: strengths and weaknesses as well as opportunities and threats

Process Chain for Numerical Simulation of IMLS

Additive layer manufacturing methods imply, among other advantages, extensive flexibility concerning their ability to realize mass customization. Despite various efforts towards process enhancement, numerous deficiencies concerning part distortion or residual stresses are still observable. The present work deals with the definition of an efficient process chain for numerical simulation of indirect metal laser sintering (IMLS), in order to improve dimensional accuracy. The underlying method is based on investigations of dilatometric behavior of iron based powder, which is integrated into reaction kinetic models and coupled with a finite element analysis (FEA). Thus, singular process steps, e. g. solid phase sintering, phase transformations or infiltration, are numerically modelled with adequate accuracy. Referring to thermomechanical simulation, possibilities for pre-scaling of part geometries are presented.Mechanical Engineerin