GitHub - wncc/genetic-algorithm: Having found interest in the subject, we intend to make an abstract problem solver which takes the description of a problem, as well as its restraints as inputs (these restraints include rules which govern the choice of a solution to the problem), and find out solutions to the problem using genetic algorithms. Please Note: Although the extract mentioned above is very general, we may limit ourselves to specific classes of problems, which would depend largely on the amount of time available. (For instance: Optimization Problems)

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Having found interest in the subject, we intend to make an abstract problem solver which takes the description of a problem, as well as its restraints as inputs (these restraints include rules which govern the choice of a solution to the problem), and find out solutions to the problem using genetic algorithms. Please Note: Although the extract m…

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Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
ALL_tsp		ALL_tsp
ALL_tsp.tar.gz		ALL_tsp.tar.gz
Fitness~		Fitness~
Main.py		Main.py
Main.py~		Main.py~
PlanofAction-GeneticAlgorithms(1).pdf		PlanofAction-GeneticAlgorithms(1).pdf
README		README
README~		README~
crossover.py		crossover.py
crossover.pyc		crossover.pyc
crossover.py~		crossover.py~
dj38.tsp.txt		dj38.tsp.txt
dj38.tsp.txt~		dj38.tsp.txt~
example2.txt		example2.txt
fileRead.py		fileRead.py
fileRead.py~		fileRead.py~
fileRead2.py~		fileRead2.py~
fitness.py		fitness.py
fitnessFunction.py		fitnessFunction.py
fitnessFunction.pyc		fitnessFunction.pyc
fitnessFunction.py~		fitnessFunction.py~
mutation.py		mutation.py
mutation.pyc		mutation.pyc
mutation.py~		mutation.py~
optimalTour.py		optimalTour.py
optimalTour.py~		optimalTour.py~
randomLists.py		randomLists.py
randomLists.pyc		randomLists.pyc
randomizing.py		randomizing.py
randomizing.pyc		randomizing.pyc
randomizing.py~		randomizing.py~
readInput.py		readInput.py
readInput.pyc		readInput.pyc
readInput.py~		readInput.py~
top.py		top.py
top.pyc		top.pyc
top.py~		top.py~
wi29.tsp.txt		wi29.tsp.txt

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Your system must have python installed, on linux (Ubuntu)

1. Download the zip file and extract it.
2. Now run Main.py using"$ python Main.py"
3. You can change the number of population members and the number of runs as state variables in Main.py
4. You can change the the problem that you wish to solve by copying the required file from the list of sample tsp files given in the folder ALL_tsp, and then applying that filename to the state variable in fileRead.py