Travelling salesman problem solved via genetic algorithm, Demo
npm install
npm run dev
Then navigate to http://localhost:8080
, server run by webpack-dev-server
npm run build
Will generate a bundle.js
file in the out
directory.
npm test
Solving the travelling salesman problem with genetic algorithms, a visualization
Travelling salesman problem solved via genetic algorithm, Demo
npm install
npm run dev
Then navigate to http://localhost:8080
, server run by webpack-dev-server
npm run build
Will generate a bundle.js
file in the out
directory.
npm test
Currently, the GA operators are heavily tied to the Tour class. It would be nice if we can generify this for any chromosome. Whether it's a list of numbers or a list of cities.
When actually using the uniform ordered crossover, a user won't be supplying a bitmask, rather it's expected that a randomly generated bitmask will be used.
So right now, in order to do this, one would have to do. creating a UOX strategy:
new UniformOrderedCrossover(null, bitmaskSize)
which is obviously not nice
Therefore, the bitmask should be an optional argument, positioned last within the constructor.
This change allows to make a new UOX strategy as:
new UniformOrderedCrossover(bitmaskSize)
which is nicer.
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