v1.1.2

• This version solves several bugs related to the number of function evaluations counter.
• This version adds the Latin Hypercube sampling as a new initializer.
• All the continuous optimization algorithms are now initialized using Uniform sampling.
• This version adds the Discrete Bayesian network probabilistic model.
• This version adds the Estimation of Bayesian network algorithm for categorical variables.
• This version adds the categorical variant of the UMDA approach.
• This version adds the categorical data initializer.
• This version solves several issues related to the documentations.
• This version allows to use different upper and lower bounds in each of the dimensions of the algorithm.
• This version removes old versions of discrete EDAs related to time series selection. Now can be implemented with new and more efficient versions.