Week--9 & 10

  1. Hill Climbing and Simulated Anealing: In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. John Holland introduced genetic algorithms in 1960 based on the concept of Darwin’s theory of evolution; his student David E. Goldberg further extended GA in 1989.

  2. Genetic Algorithm: A genetic algorithm is a search heuristic that is inspired by Charles Darwin's theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation.

Download Files

lecture-17-18.pptx (0.63 MB )

ga.pptx (0.19 MB )

https://drive.google.com/drive/u/1/folders/0B74Ehg-8NLQWfmZvMEhWYnFfTHhtN1dnY051SHZROUxha2lyYVMyNU1HSGdVSHBoTE9Fclk