Evolutionary Search for Smooth Maps in Motor Control Unit Calibration

We study the combinatorial optimization task of choosing the smoothest map from a given family of maps, which is motivated from motor control unit calibration. The problem is of a particular interest because of its characteristics: it is NP-hard, it has a direct and important industrial application, it is easy-to-state and it shares some properties of the wellknown Ising spin glass model. Moreover, it is appropriate for the application of randomized algorithms: for local search heuristics because of its strong 2-dimensional local structure, and for Genetic Algorithms since there is a very natural and direct encoding which results in a variable alphabet. We present the problem from two points of abstract view with a very simple definition of smoothness and the real-world application. We run local search, Genetic and Memetic Algorithms. We compare the direct encoding with unary and binary codings, and we try a 2-dimensional encoding. For a simple smoothness criterion, the Memetic Algori...

• Type: Conference
• Year: 2001
• Where: SAGA
• Authors: Jan Poland, Kosmas Knödler, Alexander Mitterer, Thomas Fleischhauer, Frank Zuber-Goos, Andreas Zell
• Keywords: Control Systems, Direct Encoding, Genetic Algorithm, Local Search, SAGA 2001