315 - Optimization using Genetic Algorithm

Code generated in the video can be downloaded from here: https://github.com/bnsreenu/python_fo... The genetic algorithm is a stochastic method for function optimization inspired by the process of natural evolution - select parents to create children using the crossover and mutation processes.​ Coding it in python: The algorithm consists of the following key steps:​ Initialize a population of binary bitstrings with random values.​ Decode the binary bitstrings into numerical values and evaluate the fitness (the objective function) for each individual in the population.​ Select the best individuals from the population using tournament selection based on the fitness scores.​ Create new offsprings from the selected individuals using the crossover operation.​ Apply the mutation operation on the offsprings to maintain diversity in the population.​ Repeat steps 2 to 5 until a stopping criterion is met.​ ​