Course Name: 

Genetic Algorithms (IT427)


B.Tech (AI)


Programme Specific Electives (PSE)

Credits (L-T-P): 

(3-0-2) 4


Introduction, Possible Applications, Pros and Cons, Principles of Evolutionary Processes and Genetics Introduction to Evolutionary Computation: Biological and artificial evolution, evolutionary computation and AI, different historical branches of EC, a simple genetic algorithm. Search Operators: Crossover, mutation, crossover and mutation rates, Crossover for real-valued representations, mutation for real-valued representations, combinatorial GA, Selection Schemes: Fitness proportional selection and fitness scaling, ranking, tournament selection, selection pressure and its impact on evolutionary search. Theoretical Analysis of Evolutionary Algorithms: Schema theorems, convergence of the algorithms, computational time complexity of the algorithms, no free lunch theorem. Search Operators and Representations: Mixing different search operators, adaptive representations. Niching and Speciation: Fitness sharing, crowding and mating restriction. Constraint Handling: Common techniques, penalty methods, repair methods, Deb's penalty parameter method. Multiobjective evolutionary optimization: Pareto optimality, multi-objective evolutionary algorithms: MOGA, NSGA-II, etc. Applications of GA in engineering problems, job-shop scheduling and routing problems. Evolutionary robotics and evolutionary hardware: Evolving control. Evolving morphology. Body-brain co-evolution. Evolution in simulation and in reality. The case for and against simulation.


Goldberg D.E. Genetic Algorithms in Search, Optimization and Machine Learning. Pearson Education Asia 2002
K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, Wiley and Sons, 2009.
M. Mitchell, An introduction to genetic algorithms, MIT Press, 1996.
L. D. Davis, Evolutionary algorithms, Springer-Verlag, 1999.
Evolutionary Computation: A Unified Approach by Kenneth A. DeJong, MIT Press, 2006, ISBN: 0262041944
Bäck, T, 2000. Evolutionary Computation 1: Basic Algorithms and Operators. Institute of Physics Publishing, Bristol.
Jacob, C., 2001. Illustrating Evolutionary Computation with Mathematica. Morgan Kaufmann.


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