Genetic Algorithms
AI · Intermediate
Definition
Genetic algorithms evolve a population of solutions using selection, crossover and mutation.
Optimize problems where gradients are unavailable.
Diagram
Flowchart
Example: Single-point crossover
a, b, cut = '11111', '00000', 2
print(a[:cut] + b[cut:], b[:cut] + a[cut:])Output: 11000 00111
Key points
- Mutation keeps diversity
- No guarantee of global optimum
Interview questions
Why mutation?
It explores new solutions and avoids getting stuck.