Monthly Archives: March 2017

CfP: Multidisciplinary Design #Optimisation @EUROGEN2017

Across all fields of Engineering Sciences, many design problems are multidisciplinary in nature. An optimal design can be achieved if all the disciplines are concurrently considered in an integrated approach. In MDO the whole is more than the sum of the parts, therefore the optimum of the integrated problem is superior to the design found by optimizing each discipline independently. However, including all disciplines simultaneously significantly increases the complexity of the problem. The optimal design of each discipline can be in itself a hard and computationally intensive optimization problem. In addition, the definition of the level of fidelity of the model for each discipline, the interexchange of variables of different nature (the output of one discipline can become the input to another) and the increased dimensionality, contribute to make the problem considerably harder. The largest number of applications is in the field of aerospace engineering, such as aircraft and spacecraft design in which aerodynamics, structural analysis, propulsion, control theory, and economics are integrated in a single optimization process. But many techniques have been developed and applied in a number of different fields, including automotive design, naval architecture, electronics, computers, and electricity distribution. More:

Sequential Parameter #Optimization Toolbox SPOT 2.0.1 on CRAN #rstats

SPOT: Sequential Parameter Optimization Toolbox 2.0.1

This is a major update of the R package. The SPO toolbox provides a set of tools for model based optimization and tuning of algorithms. It includes surrogate models, optimizers and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources. See:

@GECCO2017 Call for Late-Breaking Abstracts


Two-page abstracts describing late-breaking developments in the field of genetic and evolutionary computation are solicited for presentation at the Late-Breaking Abstracts Workshop of the 2017 Genetic and Evolutionary Computation Conference (GECCO 2017), and for inclusion in the proceedings companion to be distributed on USB key to all attendees of the conference and in the ACM Digital Library.
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CfP: Uncertainty based #Optimization in Engineering @UTOPIAE_network

The deadline to submit your abstract for the sessions on “Uncertainty based Optimization in Engineering” within the framework of the 15th EUROPT Workshop on Advances in Continuous Optimization, Montreal, Canada, 12-14 July 2017, is fast approaching (Abstract submission deadline: March 15, 2017) .

EUROPT website:
Special session website:

More than 100 Free Publications #ComputationalIntelligence #Optimization on

Today, I updated my publication list. You can find more than 100 PDFs (Computational Intelligence, Optimization, Simulation, Evolutionary Algorithms, Algorithm Tuning, etc.) on

The most recent article Model-based methods for continuous and discrete global optimization
is freely available until April 11, 2017. The following link will direct you to the final version of the article on ScienceDirect (free, without personal or institutional registration)

@UTOPIAE_network @TH_Koeln: Uncertainty Treatment and OPtimisation In Aerospace Engineering

Mit “UTOPIAE – Uncertainty Treatment and OPtimisation In Aerospace Engineering” beteiligt sich die TH Köln zum vierten Mal an einem von der EU geförderten Marie-Curie-Innovations-Ausbildungsprogramm. Mit rund 3.9 Millionen Euro Fördersumme forschen europaweit 15 Doktorandinnen und Doktoranden interdisziplinär an der Optimierung der computergenerierten Konstruktion von Luft- und Raumfahrtzeugen.
Koordiniert von der Strathclyde University in Schottland arbeiten insgesamt 15 Hochschulen, Forschungseinrichtungen und Firmen in Großbritannien, Italien, Belgien, Frankreich und den USA zusammen. Darunter die Stanford University, Airbus Operations GmbH und die Deutsche Luft- und Raumfahrt. Die TH Köln übernimmt dabei Aufgabenbereiche aus der Mathematik und Informatik unter der Leitung der Professoren Dr. Thomas Bartz-Beielstein und Dr. Boris Naujoks von der Fakultät für Informatik und Ingenieurwissenschaften.

Den vollständigen Text der Pressemitteilung finden Sie unter–uncertainty-treatment-and-optimisation-in-aerospace-engineering_41808.php