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In this paper, we evaluate the application of Bayesian Optimization (BO) to discrete event simulation (DES) models. In a first step, we create a simple model, for which we know the optimal set of parameter values in advance. We implement the model in SimPy, a framework for DES written in Python. We then interpret the simulation model as a black box function subject to optimization. We show that it is possible to find the optimal set of parameter values using the open source library GPyOpt. To enhance our evaluation, we create a second and more complex model. To better handle the complexity of the model, and to add a visual component, we build the second model in Simio, a commercial off-the-shelf simulation modeling tool. To apply BO to a model in Simio, we use the Simio API to write an extension for optimization plug-ins. This extension encapsulates the logic of the BO algorithm, which we deployed as a web service in the cloud.
The fact that simulation models are black box functions with regard to their behavior and the influence of their input parameters makes them an apparent candidate for Bayesian Optimization (BO). Simulation models are multivariable and stochastic, and their behavior is to a large extent unpredictable. In particular, we do not know for sure which input parameters to adjust to maximize (or minimize) the model’s outcome. In addition, the complex models can take a substantial amount of time to run.
Bayesian Optimization is a sequential and self-learning algorithm to optimize black box functions similar to as we find them in simulation models: they contain a set of parameters for which we want to identify the optimal set, they are expensive to evaluate, and they exhibit stochastic noise. BO has proven to efficiently optimize black box functions from varius disciplines. Among those, and most notably, it is successfully applied in machine learning algorithms to optimize hyperparameters.
SimBO is a flexible framework for optimizing discrete event-driven simulations (DES) using sequential optimization algorithms. While specifically designed for Bayesian Optimization (BO) in the context of DES, SimBO can be applied to any black-box problem with other optimization algorithms. The framework consists of four encapsulated components - the black-box problem, the sequential optimization algorithm, a database for experiment configuration and results, and a web-based graphical user interface - that communicate via well-defined interfaces. Each component can be run in different environments, allowing for cooperation between different hardware- and software configurations. In our research context, SimBO’s architecture enabled BO algorithms to be run on a high-performance cluster with GPU support, while the simulation is executed on a local Windows machine using the Simio simulation software. The framework’s flexibility also makes it suitable for evolving from a research-focused tool to a production-ready, cloud-based optimization tool for modern algorithms.
Iron deficiency is a global issue and can lead to a variety of clinical pictures. The biofor-tification of vegetables with iron could complement the existing portfolio of iron-rich products, thus improving iron supply in the long term. In order to determine whether the iron-biofortified vegetables could meet this demand and would address appropriate target groups, a quantitative online survey was conducted in Germany. Based on 1000 consumer responses, a cluster analysis was performed. The results showed a four-cluster solution. The first cluster was holistically engaged, the second was fitness-affine but health unconcerned, the third cluster consists frugal eaters with a focus on medical prevention, and the fourth cluster are hedonists. No cluster focused its consumption on iron-enriched products, but instead all developed an individual mix of the three product groups.
Perceptions of German consumers regarding methods for fortifying foods with iodine (Abstract)
(2022)
Transition road maps – an investigative approach to map the daily life consumption of individuals
(2014)
The present paper aims at investigating an innovative approach to guide consumers’ daily life choices in Germany towards a more sustainable way of acting. This should be achieved by introducing a new concept: transition road maps. Transition road maps bear the capability of illustrating courses of consumption behaviour without being prohibitive. These schemes foster self-determined behaviour and encourage the consumer to rethink and restructure his or her habits of consumption, with a focus on sustainability. The innovative thought is, not to simply stick to the usual triad of spheres of activity, consisting of nutrition, mobility and housing. Instead further aspects of consumers’ daily routines are considered, such as leisure activities, time usage or financial activities. Moreover the transition road maps are based on a new ideology of combining and connecting the qualitative algorithm of time use, financial spending and resource impact of social practices in the area of private consumption. In the long-term, the transition road maps could e.g. be used in sustainability communication or consumer counselling.
Taking the transdisciplinary research study “Green fingers for a climate resilient city”, funded by the German Ministry of education and research (BMBF), as an example, this paper follows the hypothesis that processes of landscape planning and designing multifunctional green spaces and processes of co-creation need to be combined to stimulate climate resilient city transformation. The findings are that efforts to combine these processes benefit from making complex climate-resilient city planning accessible for people of different professional backgrounds. The paper showcases how storytelling (Schmidt 2019), mapping (Langner 2009) and guided walks (Schultz 2019) are means to mutually engage with, perceive and understand multifunctional green spaces, inspire ownership, and build capacity for the city’s climate-resilient transformation.
Taking the transdisciplinary research study “Green fingers for a climate resilient city”, funded by the German Ministry of education and research (BMBF), as an example, this paper follows the hypothesis that processes of landscape planning and designing multifunctional green spaces and processes of co-creation need to be combined to stimulate climate resilient city transformation. The findings are that efforts to combine these processes benefit from making complex climate-resilient city planning accessible for people of different professional backgrounds. The paper showcases how storytelling (Schmidt 2019), mapping (Langner 2009) and guided walks (Schultz 2019) are means to mutually engage with, perceive and understand multifunctional green spaces, inspire ownership, and build capacity for the city’s climate-resilient transformation.
The contribution follows the hypothesis that the concept of transformative resilience can be a driver in transdisciplinary processes bringing together landscape planning and landscape design. Combining processes of generating, structuring and spatializing knowledge on landscape functions and designing visions for sustainable landscapes on different scales benefits from the creative use of mappings.
Wood fibers can contribute to replacing peat in growing media and thus help to protect peatlands. As domestic, renewable raw materials, they represent a sustainable option for this purpose. To date, however, wood fibers are usually used as a peat substitute at a maxi-mum of 30% (v/v). A main reason for this limitation is the insufficient microbial stability of wood fibers, which favors nitrogen immobilization and can thus impair nitrogen supply of plants. To address this drawback, in this study wood fibers were subjected to different thermal or thermal-hydrolytic treatments. Seedling tests with napa cabbage were conducted to determine whether treated wood fibers were free of phytotoxic substances. Mixtures with 50% (v/v) wood fiber and white peat each were used. In addition, three wood fiber varieties were evaluated in the cultivation of petunia. Two wood fiber proportions (30 and 60% v/v) and two nitrogen fertilization rates (common and increased supply) were included in each case. In the seedling trial with napa cabbage, no phytotoxic effects were detectable in any of the wood fiber variants investigated. However, when cultivating petunias, both shoot mass growth and number of flowers decreased with increasing wood fiber content. In substrates with a wood fiber content of 60% (v/v), plant development was inhibited so severely that the petunias no longer achieved marketable quality. Increased nitrogen fertilization was able to compensate for this negative effect only in few cases. This suggests that other factors than nitrogen limited plant growth in wood fiber-rich substrates. Among others, physical proper-ties such as the lower water capacity of wood fibers may be a cause. More in-depth investigations are still required in this regard.