Intermediate · Research
Genetic algorithm (GA)
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. An optimization technique inspired by natural selection, using processes like mutation and crossover to find solutions to complex problems.
Technical Definition
An optimization technique inspired by natural selection, using processes like mutation and crossover to find solutions to complex problems.
How it works
Genetic algorithms mimic biological evolution to solve search and optimization problems. They start with a population of potential solutions and iteratively apply operators like selection, crossover, and mutation to evolve better solutions over generations.
Related Concepts
- Optimization — The mathematical process of finding parameter values that minimize a loss function.
- Evolutionary algorithm (EA) — An optimization algorithm inspired by biological evolution, using processes like selection and mutation to find solutions.
- Metaheuristic — A high-level strategy that guides a search algorithm to find good solutions for complex optimization problems, especially with limited resources.