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Upon successful completion of this course, students will be able to:
Module-I (5 Hours)
Non Linear Constrained Optimization Problem: Constrained optimization using Lagrange Method, Lagrange Multiplier Equality Constraints, Constrained optimization using Kuhn Tucker Method, Kuhn Tucker inequality Constraints.
Practice-1: (2 Hours)
Solving minimization constrained optimization problem using python
Practice-2: (2 Hours)
Solving maximization constrained optimization problem using python
Module-II (5 Hours)
Direct Search Method for Unconstrained Optimization Problem: Univariate Search Method, Golden Section Search Method and Application of Golden Section Search Method.
Practice-3: (2 Hours)
Solving nonlinear system of equations using Python
Module-III (4 Hours)
Gradient Method for Unconstrained Optimization Problem: Gradient Descent Method, Algorithm for Gradient Descent Method, Steepest Descent Gradient Method.
Practice-4: (2 Hours)
Implementing Gradient Descent algorithm in Python
Practice-5: (2 Hours)
Linear Regression using Gradient Descent in Python
Module-IV (4 Hours)
Sequencing Models: Problems with n' Jobs through Two Machines, Problems with 'n' Jobs through Three Machines, Problems with Two Jobs through 'm' Machines.
Module-V (4 Hours)
Particle Swarm Optimization: Particle Swarm Optimization Theory, Particle Swarm Optimization Algorithm, Application of Particle Swarm Optimization,
Practice-6 & 7: (2+2 Hours)
Implementing the Particle Swarm Optimization (PSO) Algorithm in Python
Module-VI (4 Hours)
Game with Pure Strategy: Game and Strategy, Maximin-Minimax principle, Two person zero-sum game with Saddle Point, Solving matching coin problem using game theory.
Module-VII (4 Hours)
Game with Mixed Strategy: Mixed Strategy Game, Game without Saddle Point, Graphical Method to Solve Mixed Strategy Game, Dominance Principle to Solve Mixed Strategy Game.
Kanti Swarup, P.K. Gupta and Man Mohan-Operations Research, S. Chand and Co. Pvt.Ltd.
Engineering Optimization Theory and Practice by Singiresu S. Rao, JOHN WILEY & SONS, INC., Fourth Edition
Mathematical Programming by N. S. Kambo, East West Press.
Lagrange Multiplier Equality Constraints
Kuhn Tucker inequality Constraints and its problems dicussion
Application of Golden Section Search Method
Dr. Mohammed Siddique, received Ph. D in Mathematics in the area of Optimization Techniques and Machine Learning from KIIT, Deemed to be University, Bhubaneswar and completed his M.Sc in Mathematics and M.Tech in Computer Science from Utkal University, Bhubaneswar. He is having more than 16 years of teaching experience. He is having more than 50 […]