It is shown by means of Markov chain analysis that unimodal binary long-path problems can be solved by mutation and elitist selection in a polynomially bounded number of trials on average.

Simulated annealing and single-trial versions of evolution strategies possess a close relationship when they are designed for optimization over continuous variables. Analytical investigations of their differences and similarities lead to a cross-fertilization of both approaches, resulting in new theoretical results, new parallel population-based algorithms, and a better understanding of the interrelationships.