1. Genetic algorithms are stochastic optimization algorithms inspired by natural evolution that use operations like selection, crossover and mutation to evolve solutions to problems. 2. They work on a population of potential solutions, evaluating their fitness to survive and reproduce, with reproduction combining traits of parents to form new potential solutions over generations. 3. Genetic algorithms find wide applications in function optimization, multi-objective optimization, scheduling, image processing, engineering design and other domains requiring search and optimization.

1. A Demonstration By: SAFI UR REHMAN PhD Scholar at Department of Mining Engineering GENETIC ALGORITHMS - A GENTLE INTRODUCTION

7. local global I am not at the top. My high is better! I am at the top My Height is .. I will continue 02/05/10 14:07 Genetic Algorithms – A gentle Introduction Search for Optimization

8. 02/05/10 14:07 Genetic Algorithms – A gentle Introduction Optimization

16. Randomly generate a population of potential solutions Evaluate fitness of population members Select two parents from population based on fitness Produce two children Evaluate children Crossover and mutation Is solution "Good“? Output best solution found Multiple Repeats in one iteration No Yes Genetic Algorithms Flowchart

17. 02/05/10 14:07 Genetic Algorithms – A gentle Introduction Phenotype x Genotype g Gen. Phen. Mapping Population Objective Function f i Population Pop Cross over Mutation Genotype g Initial Population Create an initial population of random individuals

19. 02/05/10 14:07 Genetic Algorithms – A gentle Introduction A Simple Example of Genetic Algorithms

20. 02/05/10 14:07 Genetic Algorithms – A gentle Introduction 2 1 n 3 Area is Proportional to fitness value 4 Roulette Wheel Selection Individual i will have a probability to be chosen

21. 02/05/10 14:07 Genetic Algorithms – A gentle Introduction 10011 101 11101 000 10011 000 Parent A Child of A and B Parent B Crossover Operator A Simple Example of Genetic Algorithms

22. 02/05/10 14:07 Genetic Algorithms – A gentle Introduction A Simple Example of Genetic Algorithms

25. T H A N K S