Randomized search heuristics like local search, tabu search, simulated annealing or all kinds of evolutionary algorithms have many applications. However, for most problems the best worst-case expected run times are achieved by more problem-specific algorithms. This raises the question about the limits of general randomized search heuristics. Here a framework called black-box optimization is dev...

In solving optimization problems, objective functions generally need to be minimized or maximized. However, cannot always formulated explicitly in a mathematical form for complicated problem settings. Although several regression techniques infer the approximate forms of functions, they are at times expensive evaluate. Optimal points "black-box" computed such scenarios, while effectively using s...

Data gathered from real world processes include several undesired effects, like the noise in the process, the bias of the sensors and the presence of hysteresis, among other undesirable uncertainty sources. Learning models using the so called Low Quality Data (LQD) is a difficult task which has been barely studied. In a previous study, a method for learning white box models in the presence of L...

Catchment models are by definition simplified representations of the real world system. This aggregation takes place in space and time and has several important consequences. First, there are no generally applicable rules to perform this aggregation, and the resulting model structure is usually a function of the modeller’s hydrological understanding. Secondly, the model parameters cannot be mea...

The q-Gaussian distribution is known to be an attractor of certain correlated systems, and is the distribution which, under appropriate constraints, maximizes the entropy Sq , the basis of nonextensive statistical mechanics. This theory is postulated as a natural extension of the standard (Boltzmann-Gibbs) statistical mechanics, and may explain the ubiquitous appearance of heavy-tailed distribu...

We revisit Gaussian Adaptation (GaA), a black-box optimizer for discrete and continuous problems that has been developed in the late 1960’s. This largely neglected search heuristic shares several interesting features with the wellknown Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and with Simulated Annealing (SA). GaA samples single candidate solutions from a multivariate normal dis...

In practical applications, one can take advantage of metaheuristics in different ways: To simplify, we can say that metaheuristics can be either used out-of-the-box or a custom version can be developed. The former way requires a rather low effort, and in general allows to obtain fairly good results. The latter implies a larger investment in the design, implementation, and fine-tuning, and can o...

BACKGROUND The dynamic rearrangements of RNA structure which occur during pre-mRNA splicing are thought to be mediated by members of the DExD/H-box family of RNA-dependent ATPases. Although three DExD/H-box splicing factors have recently been shown to unwind synthetic RNA duplexes in purified systems, in no case has the natural biological substrate been identified. A duplex RNA target of partic...

We show how the “Equation-Free” approach for multi-scale computations can be exploited to systematically study the dynamics of neural interactions on a random regular connected graph under a pairwise representation perspective. Using an individual-based microscopic simulator as a black box coarse-grained timestepper and with the aid of simulated annealing we compute the coarse-grained equilibri...