The proposed tutorial on Genetic Algorithms is designed to provide the basic exposure in Genetic Algorithms to graduate students and practicing engineers at large. The lectures will be decomposed into three sessions, and the organization for this session will be as follows: 

 Session 3 (Combination of Genetic Algorithms and Neural Nets)

Preliminaries of Neural Networks. Training of neural Networks with Genetic Algorithms. Combination of Neural Networks, Genetic Algorithms and Gradient based methods. Evolving Neural Nets of flexible architecture. Neural Network evolution with single objective Genetic Algorithms, Neural Network evolution with Multi-objective Genetic Algorithms.

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1. Genetic algorithms: Explanation of basic ideas (tutorial lecture part I)
2. Genetic algorithms: Multi-objective methods (tutorial lecture part II)
3. Tailor-made material design: An evolutionary approach using multi-objective genetic algorithms
4. Genetic algorithm based search on the role of variables in the work hardening process of multiphase steels
5. Modeling of recrystallization in cold rolled copper using inverse cellular automata and genetic algorithms
6. Genetic algorithm based multi-objective optimization of an ironmaking rotary kiln