Professor Schwefel's Keynote At EvoStar
His first post is a short summary concerning the opening keynote given by Professor Hans-Paul Schwefel, see it here.
His recent post summarizes a little bit more the keynote presented by Professor Schwefel, see here.
Very interesting posts!
Upon the future of evolutionary computation, Professor Schwefel said that "the unexpected should be expected".
Professor Schwefel also mentioned a situation when a paper reviewer commented the following: "Why should other optimization algorithms be necessary?" This comment is strongly correlated to traditional optimization methods and the development of the evolution strategies, since some researchers - along the 1960s and 1970s - thought that gradient-based methods and others techniques (such as Gauss-Seidel method) were all the stuffs they needed.
He also spoke of the application of evolution strategies (under the form of the so-called experimental optimization) to a two-phase flashing nozzle optimization, which was performed without computers! Even today, it is not possile to calculate what happens within such nozzle: thermodynamically far away from equilibrium, drag between slow water droplets and fast steam, three-dimensional turbulent boundary layer with liquid sublayer, supersonic behind nozzle throat, etc.
There were several challenges to be overtaken when preparing the grounds to the evolution strategy, such as self-adaptation, non-elitist selection method, parallelism, and so on. He obtained inspiration in natural systems to implement solutions to those problems.
An important comment that evolutionary computation researchers should pay attention:
"He's commented that evolutionary algorithms are getting less bio-inspired in time, this is not good or bad, but it's more interesting for him to look at models than to have super-tweaked ultra-tuned purportedly bio-inspired algorithms."
Labels: Conference, Evolution Strategy, Evolutionary Algorithm, Evolutionary Computation, Experimental Optimization, Hans-Paul Schwefel, Juan Julián Merelo Guervós, Old School, Pioneer, Self-Adaptation