Phone+91 9937999335

Course Coordinator

Prof. Lopamudra Mitra

Brief Description of the course:

Introduction to formulating and solving optimization problems in engineering. Single- and multi-variable optimization. Decision making and mathematical problem formulation. Formulating and solving linear optimization problems. Formulating and solving integer and mixed-integer optimization problems. Uncertainty and understanding decision making under uncertainty. Formulating and solving nonlinear optimization problems. Applications of optimization in engineering problems. Solving various optimization examples using MATLAB; students will get hands-on experience on MATLAB implementation. Students will also get an idea about ANN, Fuzzy logic Systems, PSAT & its implementation using MATLAB.

Course Content:

1- Introduction to concepts behind Optimization- Fundamentals: Understand the basic structure and process of solving optimization problems: specifically non-linear systems effectively. Identifying the problem components, identifying different types of constraints, linear& non-linear constraints, defining bounds.

2- Use of interactive tools to define and solve optimization problems.


1- Running an optimization using Optimization Tool Box in MATLAB

2- Implement an objective function as a function file. Use function handles to specify objective functions and extra data.

3- Passing extra data to objective functions.

4- Goal attainment method, Sequential quadratic Programming.

5- Hands on experience on use of optimization tool box with examples


1- Application of Evolutionary Algorithms to different problems ELD.

2- Implementation of these algorithms using MATLAB Programming.


1- Artificial Neural network(ANN): Back propagation Algorithm, Radial Basis Algorithm.

2- Estimation of performance index and design of controllers using optimisation algorithm.


1- Introduction to Fuzzy Logic.

2- Fuzzy Inference Systems, Building Systems with Fuzzy Logic Toolbox Software.

3- Simulating Fuzzy Inference Systems Using the Fuzzy Inference Engine.


1- Load flow solution using MATPOWER- PSAT.

2- Optimisation of non-linear system using evolutionary computing.

Who should attend?
EEE, AEI, ECE (6th and 8th Semester Students)
Resource persons:
1- Prof. P.K. Hota(VSSUT, Burla)
2- Prof. Saroj Kanta Misra
3- Prof. R. K. Swain
4- Prof. (Dr.) R.P. Panda
5- Prof. L.N. Pathy
6- Prof. Lopamudra Mitra
7- Prof. Seema Behera
8- Prof. S. Balita
Pre-requisite for the Course:
Knowledge of basics of Optimization Engineering
Course Outcome:

This course will help the students carry out research/ project work in Power system, Power Electronics and also apply optimization techniques to mitigate various problems of other branches/areas as well. This course gives a comprehensive knowledge about optimization & its implementation using MATLAB. This course is helpful for students and Research Scholars.


6 Days (4hrs per day)


22nd May to 27th May 2017

Course Fee:

₹ 2000