Cauchy Annealing Schedule: An Annealing Schedule for Boltzmann Selection
  Scheme in Evolutionary Algorithms
  Boltzmann selection is an important selection mechanism in evolutionary
algorithms as it has theoretical properties which help in theoretical analysis.
However, Boltzmann selection is not used in practice because a good annealing
schedule for the `inverse temperature' parameter is lacking. In this paper we
propose a Cauchy annealing schedule for Boltzmann selection scheme based on a
hypothesis that selection-strength should increase as evolutionary process goes
on and distance between two selection strengths should decrease for the process
to converge. To formalize these aspects, we develop formalism for selection
mechanisms using fitness distributions and give an appropriate measure for
selection-strength. In this paper, we prove an important result, by which we
derive an annealing schedule called Cauchy annealing schedule. We demonstrate
the novelty of proposed annealing schedule using simulations in the framework
of genetic algorithms.
