Programming exercises - Soft Computing course

@Harri Juutilainen

#1 Binary coded GA in python

#2 Particle swarm optimization in python

#3 Real-coded GA with 3 different methods of constraint handling

#4.1 NSGA-II, implemented nondominated sorting and crowding distance calculation

#4.2 MOEA/D, Tchebycheff and weighted sum approaches implementation

#5 FINAL PROJECT: Memetic particle swarm optimization. 4 different local search approaches.

#EXTRA review of a Genetic programming paper and a Memetic computation paper

PSO sample

Name		Name	Last commit message	Last commit date
Latest commit History 71 Commits
.vscode		.vscode
GA_result.dat		GA_result.dat
MOEAD_result.dat		MOEAD_result.dat
MPSO_result.dat		MPSO_result.dat
MPSO_scheme_1.dat		MPSO_scheme_1.dat
MPSO_scheme_1.mp4		MPSO_scheme_1.mp4
MPSO_scheme_2.dat		MPSO_scheme_2.dat
MPSO_scheme_2.mp4		MPSO_scheme_2.mp4
MPSO_scheme_3a.dat		MPSO_scheme_3a.dat
MPSO_scheme_3a.mp4		MPSO_scheme_3a.mp4
MPSO_scheme_3b.dat		MPSO_scheme_3b.dat
MPSO_scheme_3b.mp4		MPSO_scheme_3b.mp4
NSGA2_result.dat		NSGA2_result.dat
PSO_result.dat		PSO_result.dat
RCGA_result.dat		RCGA_result.dat
README.md		README.md
programming_exercise_1.py		programming_exercise_1.py
programming_exercise_2.py		programming_exercise_2.py
programming_exercise_3.py		programming_exercise_3.py
programming_exercise_4_MOEAD.py		programming_exercise_4_MOEAD.py
programming_exercise_4_NSGA2.py		programming_exercise_4_NSGA2.py
programming_exercise_final.py		programming_exercise_final.py
pso.gif		pso.gif
review.pdf		review.pdf