Non Linear Programming Problem For Academics and Research

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Engineering Vidya

5:23:00

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1 - Prerequisites1 Computation of Determinant

1 - 1.Determinant.pdf

1 - Detrminant of 2x2.mp4

03:05

2 - Determinant of 3x3.mp4

12:47

3 - Determinant of 4x4.mp4

13:12

4 - Determinant of 5x5.mp4

15:41

2 - Prerequisites2 Partial Differentiation Evaluation

5 - Partial Differentiation of Linear Function.mp4

13:11

6 - Partial Differentiation of NonLinear Function.mp4

10:25

7 - Examples-on-Partial-Differentiation.pdf

7 - Partial Differentiation of Lagranges Function.mp4

09:40

3 - Introduction of NLPP

8 - Introduction of NLPP.mp4

04:49

9 - Difference between LPP and NLPP.mp4

03:05

10 - Classification of NLPP Problem.mp4

02:08

4 - Exercise1 Calculation of Relative Maxima and Relative Minima

11 - Analysis of Exercise1.mp4

00:44

12 - Procedure to Calculate relative Maxima and relative Minima.mp4

04:54

13 - Solution of Exercise1 1.mp4

04:25

14 - Exercise-1.pdf

14 - Solution of Exercise1 1.mp4

07:39

15 - Solution of Exercise1 3.mp4

05:05

16 - Solution of Exercise1 3.mp4

07:47

5 - Exercise2 Lagrangian Multiplier with Two variable and One Constraint

17 - Roadmap of Exercise2.mp4

01:24

18 - Analysis of Exercise2.mp4

01:11

19 - Procedure to Solve NLPP using Lagrangian Multiplier 2V1C.mp4

03:44

20 - Solution of Exercise2 1.mp4

09:46

21 - Exercise-2.pdf

21 - Solution of Exercise2 1.mp4

06:25

6 - Exercise3 Lagranigian Multiplier with Three Variables and One Constraint

22 - Roadmap of Exercise3.mp4

01:20

23 - Analysis of Exercise3.mp4

01:14

24 - Procedure to Solve NLPP using Lagrangian Multiplier3V1C.mp4

05:47

25 - Solution of Exercise3 1.mp4

12:37

26 - Exercise-3.pdf

26 - Solution of Exercise3 1.mp4

13:28

7 - Exercise4 Lagranigian Multiplier with Two Variables and Two Constraint

27 - Roadmap of Exercise4.mp4

01:14

28 - Analysis of Exercise4.mp4

01:34

29 - Procedure to Solve NLPP using Lagrangian Multiplier2V2C.mp4

05:09

30 - Solution of Exercise4 1.mp4

11:29

31 - Exercise-4.1.pdf

31 - Solution of Exercise4 1.mp4

10:53

8 - Exercise5 Lagranigian Multiplier with Three Variables and Two Constraint

32 - Roadmap of Exercise5.mp4

01:26

33 - Analysis of Exercise5.mp4

01:15

34 - Procedure to Solve NLPP using Lagrangian Multiplier3V2C.mp4

07:45

35 - Solution of Exercise5 1.mp4

21:53

36 - Exercise-5.pdf

36 - Solution of Exercise5 1.mp4

11:52

9 - Exercise6 Kuhn Tucker Method with one Constraint

37 - Roadmap of Exercise6.mp4

01:58

38 - Analysis of Exercise6.mp4

01:30

39 - Procedure to Solve NLPP using Kuhn Tucker Method with One Constraint.mp4

05:40

40 - Solution of Exercise6 1.mp4

06:30

41 - Exercise-6.1.pdf

41 - Solution of Exercise6 1.mp4

10:11

10 - Exercise7 Kuhn Tucker Method with Two Constraint

42 - Roadmap of Exercise7.mp4

01:23

43 - Analysis of Exercise7.mp4

01:47

44 - Procedure to Solve NLPP using Kuhn Tucker Method with Two Constraint.mp4

05:40

45 - Solution of Exercise7 1.mp4

09:44

46 - Exercise-7.1.pdf

46 - Solution of Exercise7 1.mp4

28:34

Description

Non Linear Programming Problem, Maxima, Minima, Lagrangian Multiplier and Kuhn tucker Method

What You'll Learn?

After completion of this course, students will be able to: 1)Understand the Basics of NLPP and LPP. 2) Differentiate LPP and NLPP. 4) Apply appropriate methods to solve NLPP Problem. 3) Calculate Relative Maxima and Relative Minima. 4) Solve NLPP Problem with equality constraints using Lagrangian Multiplier. 5) Solve NLPP Problem with inequality constraint using Kuhn-Tucker Method

Who is this for?

Engineering Students, Management Students, Mathematics Scholar and Research Scholar

What You Need to Know?

No prerequisites are required because all prerequisites are covered in separate section at beginning before start of the course.

More details

Description
Non-Linear programming problems (NLPP), Course is designed by a team of engineering Viya and they have trained more than 10,000 students in last 19 years, In this course, All course contents and video lectures are systematically organized and all ambiguity, of course, is removed. The most beautiful thing about this course is, To learn this course you don't require any prerequisite concepts because all necessary prerequisites are cover in the course only. In NLPPÂ Course all problems are grouped into a number of exercises where each exercise contains a similar type of problem. All type of problems is solved and explained in detail with a simple approach and understandable language.
In this course, You will be going to learn all types of Non-Linear Programming Problems (NLPP) with the problem-solving approach, In NLPPÂ here we have covered the calculation of Relative maxima, Relative Minima, Lagrangian Multiplier, and Kuhn tucker Method. In the Lagrangian multiplier here, we have covered two variables one constraint, Three variables one constraint, two variables two constraints, and three variables two constraints problems. In the Kuhn-Tucker method here we have covered one Inequality and Two Inequality constraint problems.
This course is designed for Engineering Students, Management students, Mathematics scholars, and Research Schololors either from management or from the engineering field.
Course Outcome of NLPP Course is given below:-
After completion of this course, students will be able to:
1)Understand the Basics of NLPP and LPP.
2) Differentiate LPP and NLPP.
4) Apply appropriate methods to solve NLPP Problem.
3) Calculate Relative Maxima and Relative Minima.
4) Solve NLPP Problem with equality constraints using Lagrangian Multiplier.
5) Solve NLPP Problem with inequality constraint using Kuhn-Tucker Method

Who this course is for:
Engineering Students, Management Students, Mathematics Scholar and Research Scholar

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Having more than 18 years of training Experience and have trained more than 10000 students, I am qualified as Master of Engineering and PhD Pursuing in the Fields of Engineering from the reputed university of India.I have published 20+ research papers including national and International publication and 5 technical books in the field of computer science..

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