v 1.1.0

1.1.0

• Added number_of_function_evaluations field in algorithms and serialised data. This fields
  calculate the number of times individual's objectives and constraints are evaluated during an
  evolution.
• Renamed struct to specify stopping condition values. For example,
  the StoppingConditionType::MaxGeneration(MaxGeneration(250))
  can be defined as StoppingConditionType::MaxGeneration(MaxGenerationValue(250)). This is done to avoid confusion
  between the enum StoppingConditionType value and the value of the stopping condition.
• Added the following new stopping conditions: MaxFunctionEvaluations, Any and All. The first one stops the
  evolution
  after a maximum number of functon evaluations. The second and third allows to combine multiple condition. For example,
  they allow to stop the algorithm when either a specific duration or evolution number are reached (using Any).

v 1.0.0

1.0.0

• Added new Python API to generate reference points with DasDarren1998. The new class
  allows getting the weights for the NSGA3 algorithm and plotting them. See the Python
  type hints for name and description of the new class methods.
• Added AdaptiveNSGA3 to use the adaptive approach to handle the reference points. This
  implements the new algorithm from Jain and Deb (2014) (doi.org/10.1109/TEVC.2013.2281534)
  to handle problems where not all reference points intersect the optimal Pareto front. This
  helps to reduce crowding and enhance the solution quality. See the
  new example file
  and results.
• The algorithm additional data are now exported in AlgorithExport in the Export additional_data in AlgorithmExport
  field. This contains, for example, the reference points for NSGA3.

v 0.6.0

0.6.0

• Removed crate hv-wfg-sys. The hyper-volume from HyperVolumeWhile2012 is now calculated
  using the Rust implementation of the While et al. (2012) approach from the paper. No public
  API has been changed.
• Replaced GPL license with MIT license.

0.5.0

0.5.0

• Remove plot feature and plotters as dependency. Charts can now be generated via
  the Python package optirustic
• Added python API for NSGA3 to plot reference points from the algorithm's data
• Added python function plot_reference_points to plot reference points from a vector
• Updated reference point examples to use new serialise function
• Added Python scripts to plot serialised reference points
• Added new charts in example folder generated from serialised data