CMR342 Optimization Techniques Syllabus:
CMR342 Optimization Techniques Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES
1. To understand the concept in operation research
2. To learn about the linear programing
3. To understand the various methods in one dimensional and multi-dimensional
4. To obtain the knowledge in constrained and unconstrained problems
5. To understand the various methods in evolutionary programming
UNIT – I INTRODUCTION TO OPERATIONS RESEARCH
Introduction to Operations Research – assumptions of linear programming problems – Formulations of linear programming problem – Graphical method
UNIT – II LINEAR PROGRAMMING
Solutions to LPP using simplex algorithm- Revised simplex method – primal dual relationships – Dual simplex algorithm – Sensitivity analysis – Computer programming linear methods
UNIT – III ONE DIMENSIONAL AND MULTI-DIMENSIONAL
Introduction to descent methods – global convergence of decent algorithms – speed convergence –Fibonacci method – golden section search method – steepest descent – newton’s method –polynomial approximation method- computer programming in one dimensional and multi-dimensional methods
UNIT – IV UNCONSTRAINED OPTIMIZATION FOR CONSTRAINED PROBLEMS
Lagrange method – inequality constraints – KKT conditions – quadratic programming – geometric programming – separable linear programming – sequential linear programming – feasible direction method
UNIT – V EVOLUTIONARY PROGRAMMING
Genetic Engineering – Genetic Operators – Reproduction – Crossover – Mutation – Selection – Genetic Local Search – Simulated Annealing – Ant Colony Optimization – Particle Swarm Optimization
TOTAL : 45 PERIODS
COURSE OUTCOMES
At the end of the course students able to
CO1: Knowledge on the concept in operation research
CO2: Recognize about the linear programing
CO3: Analyze the various methods in one dimensional and multi-dimensional
CO4: Knowledge in constrained and unconstrained problems
CO5: Apply the various methods in evolutionary programming
TEXT BOOKS:
1. Harvey M Wagner, Principles of Operations Research: Prentice Hall of India 2010
2. Hitler Libermann, Operations Research: McGraw Hill Pub. 2009
3. Pant J C, Introduction to Optimisation: Operations Research, Jain Brothers, Delhi, 2008
REFERENCES:
1. Pannerselvam, Operations Research: Prentice Hall of India 2010.
2. Taha H A, Operations Research, An Introduction, PHI, 2008
3. Singiresu S Rao, “Engineering Optimization: Theory and Practice”, Wiley, 4th Edition, 2013.
4. David G.Luenberger, “Linear and Nonlinear Programming”, Springer Publications, 3rd Edition, 2008.
5. Hamdy A Taha, “Operations Research – An Introduction”, Pearson, 10th Edition, 2018.
6. Stephen Boyd, Lieven Vandenberghe, “Convex Optimization”, Cambridge, 2016.
7. Bertsekas, Dimitri P. “Nonlinear Programming”. 3rd Edition. Athena Scientific Press, Belmont, Massachusetts 2016