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Rigorous runtime analysis is a major approach towards understanding evolutionary computing techniques, and in this area linear pseudo-Boolean objective functions play a central role. Having an additional linear constraint is then equivalent to the NP-hard Knapsack problem, certain classes thereof have been studied in recent works. In this article, we present a dynamic model of optimizing linear functions under uniform constraints. Starting from an optimal solution with respect to a given constraint bound, we investigate the runtimes that different evolutionary algorithms need to recompute an optimal solution when the constraint bound changes by a certain amount. The classical (1+1) EA and several population-based algorithms are designed for that purpose, and are shown to recompute efficiently. Furthermore, a variant of the (1+(λ,λ))GA for the dynamic optimization problem is studied, whose performance is better when the change of the constraint bound is small.
Was wird unter „nachhaltiger Prävention“ in der Präventionsforschung verstanden? Welche guten Beispiele für nachhaltige Prävention gibt es in der Praxis? Und v. a.: Wie lässt sich Prävention in den verschiedenen Bereichen wie Kriminalität, Gewalt und Rechtsextremismus nachhaltig gestalten? Diesen Fragen will der vorliegende Sammelband nachgehen und damit der Präventionsdebatte neue Impulse verleihen. Der Band will insbesondere die nationale sowie internationale Fachdebatte konstruktiv aufgreifen, Theorie und Praxis verbinden, „good practice“ Beispiele darstellen sowie Perspektiven nachhaltiger Prävention aufzeigen. Mit diesem Themenspektrum richtet er sich sowohl an die Wissenschaft als auch an die Praxis sowie insgesamt an eine interessierte Öffentlichkeit.
We consider the subset selection problem for function f with constraint bound B that changes over time. Within the area of submodular optimization, various greedy approaches are commonly used. For dynamic environments we observe that the adaptive variants of these greedy approaches are not able to maintain their approximation quality. Investigating the recently introduced POMC Pareto optimization approach, we show that this algorithm efficiently computes a phi=(alpha(f)/2)(1 - 1/e(alpha)f)-approximation, where alpha(f) is the submodularity ratio of f, for each possible constraint bound b <= B. Furthermore, we show that POMC is able to adapt its set of solutions quickly in the case that B increases. Our experimental investigations for the influence maximization in social networks show the advantage of POMC over generalized greedy algorithms. We also consider EAMC, a new evolutionary algorithm with polynomial expected time guarantee to maintain phi approximation ratio, and NSGA-II with two different population sizes as advanced multi-objective optimization algorithm, to demonstrate their challenges in optimizing the maximum coverage problem. Our empirical analysis shows that, within the same number of evaluations, POMC is able to perform as good as NSGA-II under linear constraint, while EAMC performs significantly worse than all considered algorithms in most cases.
Three small stalagmites from Zoolithencave (southern Germany) show visible laminae, which consist of a clear and a brownish, pigmented layer pair. This potentially provides the opportunity to construct precise chronologies by counting annual laminae. The growth period of the three stalagmites was constrained by the C-14 bomb peak in the youngest part of all three stalagmites and C-14-dating of a piece of charcoal in the consolidated base part of stalagmite Zoo-rez-2. These data suggest an age of AD 1970 for the top laminae and a lower age limit of AD 1973-1682 or AD 1735-1778. Laminae were counted and their thickness determined on scanned thin sections of all stalagmites. On stalagmites Zoo-rez-1 and -2, three tracks were measured near the growth axes, each separated into three sections at prominent anchor laminae (I, II, III). Each section was replicated three times (a, b, c). For Zoo-rez-3, only one track was measured. The total number of laminae counted for Zoo-rez-1 ranges from 138 to 177, for Zoo-rez-2 from 119 to 145, and for Zoo-rez-3 from 159 to 166. The numbers agree well with the range constrained by the bomb peak and the age of the charcoal, which supports the annual origin of the laminae. The replicated measurements of the different tracks as well as the three different tracks on the stalagmites Zoo-rez-1 and-2 were cross-dated using the TSAP-Win (R) tree-ring software. This software is very useful for cross-dating because it enables to insert or delete missing or false laminae as well as identifying common pattern by shifting the series back and forth in time. However, visual inspection of the thin sections was necessary to confirm detection of missing or false laminae by TSAP-Win (R). For all three Zoo-rez speleothems, crossdating of the mean lamina thickness series was not possible due to a missing common pattern. The cross-dating procedure results in three refined chronologies for the three Zoo-rez stalagmites of ranging from AD 1821-1970 (Zoo-rez-1), AD 1835-1970 (Zoo-rez-2), and AD 1808-1970 (Zoo-rez-3).
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.
Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species-specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi-dimensional assessments are still to be recommended.
Die Mark
(2010)
HPI Future SOC Lab
(2015)
Das Future SOC Lab am HPI ist eine Kooperation des Hasso-Plattner-Instituts mit verschiedenen Industriepartnern. Seine Aufgabe ist die Ermöglichung und Förderung des Austausches zwischen Forschungsgemeinschaft und Industrie.
Am Lab wird interessierten Wissenschaftlern eine Infrastruktur von neuester Hard- und Software kostenfrei für Forschungszwecke zur Verfügung gestellt. Dazu zählen teilweise noch nicht am Markt verfügbare Technologien, die im normalen Hochschulbereich in der Regel nicht zu finanzieren wären, bspw. Server mit bis zu 64 Cores und 2 TB Hauptspeicher. Diese Angebote richten sich insbesondere an Wissenschaftler in den Gebieten Informatik und Wirtschaftsinformatik. Einige der Schwerpunkte sind Cloud Computing, Parallelisierung und In-Memory Technologien.
In diesem Technischen Bericht werden die Ergebnisse der Forschungsprojekte des Jahres 2015 vorgestellt. Ausgewählte Projekte stellten ihre Ergebnisse am 15. April 2015 und 4. November 2015 im Rahmen der Future SOC Lab Tag Veranstaltungen vor.