Course Name: Nonlinear programming

Course abstract

This course is offered to UG and PG students of Engineering/Science background. It contains methods to solve nonlinear optimization problems which includes convex programming, KKT optimality conditions, quadratic programming problems, separable methods, geometric and dynamic programming. It also covers some search techniques which are used to solve nonlinear programming problems. It plays a vital role in solving various engineering and science problems.


Course Instructor

Media Object

Prof. S. K Gupta

Dr.S.K.Gupta is an Associate Professor in the Department of Mathematics, IIT Roorkee. His area of expertise includes Nonlinear and Fuzzy optimization. He has guided three PhD theses and has published more than 40 papers in various international journals of repute. He has also developed a NPTEL online certification course on Mathematical methods and its applications (jointly with Prof. P. N. Agrawal).


More info

Teaching Assistant(s)

SCINDHIYA LAXMI

M.Sc., Mathematics and Scientific Computing, NIT Allahabad

 Course Duration : Jul-Aug 2017

  View Course

 Syllabus

 Enrollment : 17-May-2017 to 24-Jul-2017

 Exam registration : 02-Aug-2017 to 23-Aug-2017

 Exam Date : 24-Sep-2017

Enrolled

1342

Registered

Certificate Eligible

33

Certified Category Count

Gold

6

Elite

21

Successfully completed

6

Participation

5

Success

Elite

Gold





Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 3 out of 4 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score.
Nonlinear programming - Toppers list

DEBOPAM GHOSH 99%

AMDER

DUBEY VARSHIT SHAILENDRA 97%

GOVERNMENT COLLEGE OF ENGINEERING PUNE COEP

Enrollment Statistics

Total Enrollment: 1342

Registration Statistics

Total Registration : 42

Data Not Found..!

Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.