A connectionist machine for genetic hillclimbing
A connectionist machine for genetic hillclimbing
The role of selective pressure when solving symmetric functions in polynomial time
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
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The class of symmetric functions is based on the OneMax function by a subsequent assigning application of a real valued function. In this work we derive a sharp boundary between those problem instances that are solvable in polynomial time by the Metropolis algorithm and those that need at least exponential time. This result is both proven theoretically and illustrated by experimental data. The classification of functions into easy and hard problem instances allows a deep insight into the problem solving power of the Metropolis algorithm and can be used in the process of selecting an optimization algorithm for a concrete problem instance.