On Simulated Annealing Dedicated to Maximin Latin Hypercube Designs
  The goal of our research was to enhance local search heuristics used to
construct Latin Hypercube Designs. First, we introduce the \textit{1D-move}
perturbation to improve the space exploration performed by these algorithms.
Second, we propose a new evaluation function $\psi_{p,\sigma}$ specifically
targeting the Maximin criterion.
  Exhaustive series of experiments with Simulated Annealing, which we used as a
typically well-behaving local search heuristics, confirm that our goal was
reached as the result we obtained surpasses the best scores reported in the
literature. Furthermore, the $\psi_{p,\sigma}$ function seems very promising
for a wide spectrum of optimization problems through the Maximin criterion.
