Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that
explore the space of potential solutions by building and sampling explicit probabilistic …

The previous chapter has discussed how hierarchy can be used to reduce problem
complexity in black-box optimization. Additionally, the chapter has identified the three …

The Goemans--Williamson randomized algorithm guarantees a high-quality approximation
to the MAX-CUT problem, but the cost associated with such an approximation can be …

Large numbers of ground states of three-dimensional (3D) Edwards-Anderson Ising spin
glasses are calculated for sizes up to 10 3 using a combination of a genetic algorithm and …

Using advanced numerical approaches based on optimization algorithms, much progress
has been achieved for the study of the ground-state and low-temperature behavior of two …

We investigate the critical behavior of three-dimensional random-field Ising systems with
both Gauss and bimodal distribution of random fields and additional the three-dimensional …

We propose a new optimization method based on a demagnetization procedure well known
in magnetism. We show how this procedure can be applied as a general tool to search for …

Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that
explore the space of potential solutions by building and sampling probabilistic models of …

Monte Carlo simulation techniques, like simulated annealing and parallel tempering, are
often used to evaluate low-temperature properties and find ground states of disordered …

The investigation of genetic and evolutionary algorithms on Ising model problems gives
much insight into how these algorithms work as adaptation schemes. The one-dimensional …