- Single-point crossover allows either parent to have their genes come first now.
- Rounding to integers is doing with an additional +/- 0.5 random value so that integer genes do not get stuck at one value when rounding at the midpoint of two integers e.g. 0.5 now randomly rounds to 0 or 1 instead of always 0.
- Added weighted methods. (default setting does not change).
- Removed unnecessary exception catching. Letting exceptions flow through instead, and let the user decide how to handle them.
- Removed list conversion.
- Removed parent sorting for extrapolate.
- Simplified variable names.
Overall cleaned up a lot of comments.
EasyGA:
- Code cleanup.
Population:
- Added sort_by_best_fitness
- Added parent/mating pool methods.
- Renamed some methods for consistency.
Chromosome:
- Added get_gene(index).
Parent Selection:
- Improved selection methods to use the ga.selection_probability so that the roulette selection actually works well.
- Added stochastic selection.
Survivor Selection:
- Added fill_in_random and fill_in_parents_then_random.
Crossover/Mutation:
- Cleaned up code.
Crossover/Mutation:
- Split into individual and population subclasses.
- Added sequential population crossover selection.
- Renamed and reimplemented mutation methods.
EasyGA:
- Improved make_obj methods for the chromosomes and populations to take arguments.
Initialization:
- Improved to shorter code.
- Fixed repeated error messages
Chromosome:
- Changed get/set_genes to get/set_gene_list.
1. Deleted duplicate functions in EasyGA
2. Added new index-dependent fitness example
3. GA now auto-sorts by best fitness immediately after the fitness is calculated across the board
4. Removed 'selected' status flag from the Chromosome flag
5. Added mating_pool attribute to the population
6. Changed other code to be in line with 4 and 5
7. Optimized tournament selection method
