In this paper, we present a Multi-Surrogates Assisted Memetic Algorithm (MSAMA) for solving optimization problems with computationally expensive fitness functions. The essential backbone of our framework is an evolutionary algorithm coupled with a local search solver that employs multi-surrogates in the spirit of Lamarckian learning. Inspired by the notion of 'blessing and curse of uncertainty'...

Sobol indices are a widespread quantitative measure for variance-based global sensitivity analysis, but computing and utilizing them remains challenging for high-dimensional systems. We propose the tensor train decomposition (TT) as a unified framework for surrogate modeling and global sensitivity analysis via Sobol indices. We first overview several strategies to build a TT surrogate of the un...

The last two decades have seen a lot of development in the area of surrogate marker validation. One of these approaches places the evaluation in a meta-analytic framework, leading to definitions in terms of trial- and individual-level association. A drawback of this methodology is that different settings have led to different measures at the individual level. Using information theory, Alonso et...

In this paper we present a language, PEARL, for projecting annotations based on the Unstructured Information Management Architecture (UIMA) over RDF triples. The language offer is twofold: first, a query mechanism, built upon (and extending) the basic FeaturePath notation of UIMA, allows for efficient access to the standard annotation format of UIMA based on feature structures. PEARL then provi...

We present an approach to uncertainty propagation in dynamic systems, exploiting information provided by related experimental results along with their models. The approach relies on a solution mapping technique to approximate mathematical models by polynomial surrogate models. We use these surrogate models to formulate prediction bounds in terms of polynomial optimizations. Recent results on po...

Abstract Ride comfort is a relevant performance for road vehicles. The suspension system can filter vibration caused by the uneven to improve ride comfort. Optimization of vehicle has been extensively studied. As detailed models require significant computational effort, it becomes increasingly important develop an efficient optimization framework. In this work, multi-fidelity surrogate-based fr...

Surrogate-Assisted Memetic Algorithm(SAMA) is a hybrid evolutionary algorithm, particularly a memetic algorithm that employs surrogate models in the optimization search. Since most of the objective function evaluations in SAMA are approximated, the search performance of SAMA is likely to be affected by the characteristics of the models used. In this paper, we study the search performance of usi...