sc JNTUA B.TECH R 19 3-1 Syllabus For Optimization techniques (open elective-i) PDF 2022 – Cynohub


JNTUA B.TECH R 19 3-1 Syllabus For Optimization techniques (open elective-i) PDF 2022


JNTUA B.TECH R 19 3-1 Syllabus For Optimization techniques (open elective-i) PDF 2022

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You will be able to find information about Optimization techniques (open elective-i) along with its Course Objectives and Course outcomes and also a list of textbook and reference books in this blog.You will get to learn a lot of new stuff and resolve a lot of questions you may have regarding Optimization techniques (open elective-i) after reading this blog. Optimization techniques (open elective-i) has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. Optimization techniques (open elective-i) can be learnt easily as long as you have a well planned study schedule and practice all the previous question papers, which are also available on the CynoHub app.

All of the Topic and subtopics related to Optimization techniques (open elective-i) are mentioned below in detail. If you are having a hard time understanding Optimization techniques (open elective-i) or any other Engineering Subject of any semester or year then please watch the video lectures on the official CynoHub app as it has detailed explanations of each and every topic making your engineering experience easy and fun.

Optimization techniques (open elective-i) Unit One

Introduction and Classical Optimization Techniques:

Statement of an Optimization problem –design vector –design constraints –constraint surface –objective function –objective function surfaces –classification of Optimization problems. Classical Optimization Techniques: Single variable Optimization –multi variable Optimization without constraints –necessary andsufficient conditions for minimum/maximum –multivariable Optimization with equality constraints. Solution by method of Lagrange multipliers –multivariable Optimization with inequality constraints –Kuhn –Tucker conditions –Numerical examples.

Optimization techniques (open elective-i) Unit Two

Linear Programming

Standard form of a linear programming problem –geometry of linear programming problems –definitions and theorems –solution of a system of linear simultaneous equations –pivotal reduction of a general system of equations –motivation to the simplex method –simplex algorithm –Numerical examples.

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Optimization techniques (open elective-i) Unit Three

Nonlinear Programming –One Dimensional Minimization method

Introduction, Unimodal function, Elimination methods-Unrestricted Search, Exhaustive Search, Dichotomous Search, Fibonacci Method, Golden Section Method and their comparison; Interpolation methods -Quadratic Interpolation Method, Cubic Interpolation Method and Direct Root Methods –Numerical examples.

Optimization techniques (open elective-i) Unit Four

Unconstrained & Constrained Nonlinear Programming

Unconstrained Optimization Techniques: Introduction-Classification of Unconstrained Minimization Methods, General Approach, Rate of Convergence, Scaling of Design Variables; Direct Search methods-Random Search Methods, Grid Search Method, Pattern Directions, Powell’s Method and Simplex MethodConstrained Optimization Techniques: Introduction, Characteristics of a Constrained Problem, Direct Search Methods -Random Search Methods, Basic Approach in the Methods ofFeasible Directions, Rosen’s Gradient Projection Method, Generalized Reduced Gradient Method and Sequential Quadratic Programming.

Optimization techniques (open elective-i) Unit Five

Dynamic Programming

Dynamic programming multistage decision processes –types –concept of sub optimization and the principle of optimality –computational procedure in dynamic programming –examples illustrating the calculus method of solution -examples illustrating the tabular method of solution –Numerical examples.

Optimization techniques (open elective-i) Course Objectives

The student will be able to learn:
The basic concepts of Optimization
The emphasis of this course is on different classical Optimization techniques linear programming and simplex algorithms.
About optimality of balanced transportation Problems About Constrained and unconstrained nonlinear programming.
About principle of optimality and dynamic programming

Optimization techniques (open elective-i) Course Outcomes

The student gets thorough knowledge on
:Basic methods, principles in optimization
Formulation of optimization models, solution methods in optimization
Finding initial basic feasible solutions.
Methods of linear and non-linear (constrained and unconstrained) programming.
Applications to engineering problems.

Optimization techniques (open elective-i) Text Books

1. S. S. Rao, “Engineering optimization”: Theory and practice 3rd edition, New Age International (P) Limited, 1998.
2. H.S. Kasana & K.D. Kumar, “Introductory Operations Research Springer (India)”, 2004.

Optimization techniques (open elective-i) Reference Books

1. R Fletcher, “Practical Methods of Optimization” ,
2ndEdition, Wiley Publishers, 2000. 2. Jorge Nocedal and Wright S, “Numerical Optimization Springer”, 1stEdition, 1999.
3. by K.V. Mital and C. Mohan, “Optimization Methods in Operations Research and systems Analysis” 3rdEdition, New Age International (P) Limited, 1996.
4. by S.D. Sharma, “Operations Research”,Kedar Nath, 2012.
5. by H.A. Taha, “Operations Research”, 9thEdition, An Introduction Pearson, 2010.
6. G. Hadley, “Linear Programming”, Narosa, 2002.

Scoring Marks in Optimization techniques (open elective-i)

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Information about JNTUA B.Tech R 19 Optimization techniques (open elective-i) was provided in detail in this article. To know more about the syllabus of other Engineering Subjects of JNTUH check out the official CynoHub application. Click below to download the CynoHub application.

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Comments (2)

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