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Answers for “在遗传算法 TSP 演示中,贪婪交叉做了什么?”

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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.

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The Traveling Salesman Problem (TSP) is a classical optimization problem that seeks the shortest possible path through a set of nn cities, visiting each city exactly once. The video visualizes this as a route drawn over a fixed point set in a 2D plane.

Conditions: There is a finite set of nn cities.; The objective is to minimize total path length.; Each city must be visited exactly once.

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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.