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Default Sathyabama Institute of Science and Technology M.E. - Computer Aided Design SPRA5301 Advanced Optimization Method Syllabus

Sathyabama Institute of Science and Technology M.E. - Computer Aided Design SPRA5301 Advanced Optimization Method Syllabus

SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF MECHANICAL ENGINEERING

SPRA5301 ADVANCED OPTIMIZATION METHODS
L T P Credits Total Marks
3 * 0 3 100

UNIT 1 INTRODUCTION TO OPTIMIZATION 9 Hrs.
Engineering Applications of Optimization - Classification of Optimization Problems - Applications of Linear Programming –
Problem Formulation-Standard Form of a Linear Programming Problem -Geometry of Linear Programming Problems-
Solution by Simplex method- Sensitivity Analysis- Applications of Computer Soft wares used in Optimization problems.

UNIT 2 MINIMIZATION METHODS 9 Hrs.
Introduction - Unimodal Function –Elimination Methods - Unrestricted Search - Search with Fixed Step Size - Search with
Accelerated Step Size - Exhaustive Search - Dichotomous Search- Interval Halving Method - Fibonacci Method - Golden
Section method - Comparison of Elimination Methods.

UNIT 3 DECISION ANALYSIS 9 Hrs.
Decision Trees, Utility theory, Multi Objective Optimization, MCDM - Analytic Hierarchy Process (AHP), Analytic Network
Process (ANP), Dynamic Programming - Multistage Decision Processes.

UNIT 4 UNCONSTRAINED OPTIMIZATION METHODS 9 Hrs.
Multi variable unconstrained optimization techniques: Direct search methods: Random search method univariate method,
pattern search method, rosenbrock's method of rotating coordinate, steepest descent method and Conjugate gradient
method.

UNIT 5 HEURISTIC ALGORITHM 9 Hrs.
Genetic Algorithms, Simulated Annealing, Neural Network, Optimization using fuzzy systems, Tabu Search and Scatter
Search, Ant colony algorithm, Multi Response optimization - Gray Relational Analysis.
Max. 45 Hrs.

COURSE OUTCOMES
On completion of the course, student will be able to
CO1 - Feasibility study for solving an optimization problem.
CO2 - Evaluate and measure the performance of an algorithm.
CO3 - Understand optimization techniques using algorithms.
CO4 - To design algorithms, the repetitive use of which will lead reliably to finding an approximate solution.
CO5 - Describe clearly a problem, identify its parts and analyze the individual functions.
CO6 - Investigate, study, develop, organize and promote innovative solutions for various applications.

TEXT / REFERENCE BOOKS
1. Rao, Singaresu, S., “Engineering Optimization – Theory & Practice”, New Age International (P) Limited, New Delhi,
2000.
2. Kalyanmoy Deb, “Optimization for Engineering Design: Algorithms and Examples”, Prentice-Hall of India Private Limited,
2005.
3. Kalyanmoy Deb, “Multi-Objective Optimization Using Evolutionary Algorithms”, Wiley, 2009.
4. Lihui Wang, Amos H. C. Ng, Kalyonmoy Deb, “Multi-Objective Evolutionary Optimisation for Product Design and
Manufacturing”, Springer-Verlag London Limited, 2011.
5. Ravindran – Phillips –Solberg, “Operations Research – Principles and Practice”, John Wiley India, 2006.

END SEMESTER EXAMINATION QUESTION PAPER PATTERN
Max. Marks: 100 Exam Duration: 3 Hrs.
PART A: 5 Questions of 6 marks each – No choice 30 Marks
PART B: 2 Questions from each unit of internal choice; each carrying 14 marks 70 Marks
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