The Machine Learning Playground implements two approaches for TSP: a genetic algorithm and a method based on an elastic neural network together with a self-organization map. The video primarily demonstrates the genetic-algorithm page in detail.
Conditions: The context is the Machine Learning Playground TSP demo.; The approaches are implemented as interactive web pages.
The Machine Learning Playground implements two approaches for TSP: a genetic algorithm and a method based on an elastic neural network together with a self-organization map. The video primarily demonstrates the genetic-algorithm page in detail.
Conditions: The context is the Machine Learning Playground TSP demo.; The approaches are implemented as interactive web pages.
In the genetic-algorithm TSP demo, greedy crossover uses a heuristic rule that tries to choose the nearest unvisited city as the next move. This approach is presented as a way to quickly obtain an effectively short route.
Conditions: Used inside the genetic-algorithm TSP implementation.; The crossover option is enabled (greedy crossover: true).; At each step, the next city is chosen by nearest-unvisited-city preference.
In the genetic-algorithm TSP demo, greedy crossover uses a heuristic rule that tries to choose the nearest unvisited city as the next move. This approach is presented as a way to quickly obtain an effectively short route.
Conditions: Used inside the genetic-algorithm TSP implementation.; The crossover option is enabled (greedy crossover: true).; At each step, the next city is chosen by nearest-unvisited-city preference.