IS4003 Optimization Techniques Syllabus:

IS4003 Optimization Techniques Syllabus – Anna University PG Syllabus Regulation 2021

COURSE OBJECTIVES:

 To understand the non-linear problem.
 To know about multi-objective problem.
 To create awareness of Meta heuristic algorithms.

UNIT I INTRODUCTION

Classification of optimization problems, concepts of design vector, Design constraints, constrains surface, objective function surface and multi-level optimization, parametric linear programming

UNIT II DECISION ANALYSIS

Decision Trees, Utility theory, Game theory, Multi Objective Optimization, MCDM- Goal Programming, Analytic Hierarchy process, ANP

UNIT III NON-LINEAR OPTIMIZATION

Unconstrained one variable and multi variable optimization, KKT Conditions, Constrained optimization, Quadratic programming, Convex programming, Separable programming, Geometric programming, Non-Convex programming

UNIT IV NON-TRADITIONAL OPTIMIZATION -1

Classes P and NP, Polynomial time reductions, Introduction to NP- Hard problems, Overview of Genetic algorithms, Simulated Annealing, neural network based optimization.

UNIT V NON-TRADITIONAL OPTIMIZATION -2

Particle Swarm optimization, Ant Colony Optimization, Optimization of Fuzzy Systems.

TOTAL: 45 PERIODS

COURSE OUTCOMES:

 The students will gain familiarity with some of the well-known optimization techniques and their applicability in a real setting.
 The students will gain awareness on the usefulness and limitation of optimization.

REFERENCES

1. Christos H. Papadimitriou, Kenneth Steiglitz, Combinatorial Optimization, PHI 2006
2. Fredrick S.Hillier and G.J.Liberman, “Introduction to Operations Research”, McGraw Hill Inc. 1995.
3. Kalymanoy Deb, “Optimization for Engineering Design”,PHI,2003
4. Ravindran – Phillips –Solberg, “Operations Research – Principles and Practice”, John Wiley India, 2006.
5. Singiresu S.Rao, “Engineering optimization – Theory and practices”, John Wiley and Sons, 1996.