Engineering Tutorials

EE– 462-E GENETIC ALGORITHMS & APPLICATIONS

Theory : 100
Class work : 50

Introduction: Overview, History of evolutionary computation: Search spaces & fitness landscapes, elements of genetic algorithms, comparison of Gas and tradition search methods.

Fundamental Concepts of Gas: Typical examples to illustrate how Gas work. Simple computer exercises.

Problem Solving Using Gas: Evolving computer programs, data analysis & prediction, evolving neural networks, simple computer exercises.

Implementation of Gas: Suitability of GA for typical problems, encoding a problem for a GA, adapting the encoding, selection methods, Genetic operators, Parameters for Gas.

Text Books: 1. Davis L,”Handbook of Genetic Algorithms

2. Goldberg D.E.,”Genetic Algorithms in Search optimization & Machine Learning.”

3. Michalewiez, Z.,”Genetic Algorithms & Data Structures = Evolution Programs

Note: 8 questions are to be set –at least one from each unit. Students have to attempt any five questions in all .

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