IE3011 EVOLUTIONARY OPTIMIZATION SYLLABUS | ANNA UNIVERSITY BE INDUSTRIAL ENGINEERING 8TH SEMESTER SYLLABUS REGULATION 2008 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY 8TH SEMESTER B.E INDUSTRIAL ENGINEERING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI, TIRUNELVELI,COIMBATORE), 2008 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
IE3011 EVOLUTIONARY OPTIMIZATION L T P C
3 0 0 3
OBJECTIVE
To cover some of the evolutionary algorithms and their applications in optimization
UNIT I INTRODUCTION 9
Introduction to evolutionary computation, Evolutionary computation and AI, Historical
branches of evolutionary computation
UNIT II SEARCH SCHEMA 9
Search operators, Selection schemes, Ranking methods, Importance of
representation
61
UNIT III EVOLUTIONARY ALGORITHMS 9
Evolutionary combinatorial optimization – evolutionary algorithms, Constraint
handling
UNIT IV GENETIC PROGRAMMING 9
Genetic programming – steps, Search operators on trees, examples
UNIT V MULTIOBJECTIVE OPTIMISATION 9
Pareto optimality, Multiobjective evolutionary algorithms, Analysis of evolutionary
algorithms
TOTAL : 45 PERIODS
REFERENCES:
1. W Banzhaf et al , Genetic Programming – An introduction, Morgan Kanfmann
Publications (1999)
2. X Yao, “Evolutionary computations – Theory and Applications”, World Scientific
Publications (1999)
3. J Baeck, “Handbook of Evolutionary computation”, IOS Press, 1997.
4. Goldberg D E , Genetic Algorithms in search, optimization, Addison Wesley
(1989)
IE3011 EVOLUTIONARY OPTIMIZATION L T P C
3 0 0 3
OBJECTIVE
To cover some of the evolutionary algorithms and their applications in optimization
UNIT I INTRODUCTION 9
Introduction to evolutionary computation, Evolutionary computation and AI, Historical
branches of evolutionary computation
UNIT II SEARCH SCHEMA 9
Search operators, Selection schemes, Ranking methods, Importance of
representation
61
UNIT III EVOLUTIONARY ALGORITHMS 9
Evolutionary combinatorial optimization – evolutionary algorithms, Constraint
handling
UNIT IV GENETIC PROGRAMMING 9
Genetic programming – steps, Search operators on trees, examples
UNIT V MULTIOBJECTIVE OPTIMISATION 9
Pareto optimality, Multiobjective evolutionary algorithms, Analysis of evolutionary
algorithms
TOTAL : 45 PERIODS
REFERENCES:
1. W Banzhaf et al , Genetic Programming – An introduction, Morgan Kanfmann
Publications (1999)
2. X Yao, “Evolutionary computations – Theory and Applications”, World Scientific
Publications (1999)
3. J Baeck, “Handbook of Evolutionary computation”, IOS Press, 1997.
4. Goldberg D E , Genetic Algorithms in search, optimization, Addison Wesley
(1989)
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