What does greedy crossover do in the genetic-algorithm TSP demo?

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.

Reasoning, step by step

1. Identify the crossover mechanism in the genetic algorithm.
2. Explain the greedy rule: choose the nearest unvisited city.
3. Note the benefit: quickly yielding a short route.

Example

The narrator says, "For crossover, we use the greedy algorithms, which tries to choose the nearest unvisited city as the next move." The genetic-programming input panel shows "greedy crossover: true".

Common misconceptions

• Thinking that greedy crossover guarantees the global optimum.
• Assuming that crossover always involves random selection of the next city.

Watch the explanation

Explore next

• How large should the genetic-algorithm population be according to the video?
• Why does the video say population size 50 does not get a good solution?
• What is the Traveling Salesman Problem (TSP) as defined in the video?