Gensim
Machine Learning
Optimization algorithms inspired by natural selection that evolve solutions through mutation and crossover operations.
Detailed Explanation
Genetic Algorithms are optimization techniques inspired by natural selection, used in machine learning to find optimal or near-optimal solutions. They mimic biological evolution by evolving a population of candidate solutions through operations like mutation (random changes) and crossover (combining parts of two solutions). Over generations, the algorithm favors more effective solutions, enabling efficient problem-solving in complex search spaces.
Use Cases
- •Optimizing vehicle routing schedules to reduce delivery time and costs in logistics operations.
Related Terms
Other terms in the Machine Learning category