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FACULTY DEVELOPMENT PROGRAMME (FDP) ON NATURE INSPIRED ALGORITHMS AND THEIR APPLICATIONS

13th - 17th JULY, 2015

Mr. Hari Mohan Rai, Assistant Professor, ECE Department of Dronacharya College of Engineering, Gurgaon attended the 5 days Faculty Development Programme on the “NATURE INSPIRED ALGORITHMS AND THEIR APPLICATIONS” held from 13th - 17th JULY, 2015 at Delhi Technological University, Delhi.

The FDP programme was started with welcome address by Ms. Garima, Course Coordinator, DTU, Delhi. The Presidential Address was given by Prof. V. K. Minocha, Principal, CBPGEC, Delhi. He was the chief guest as well as one of the speaker of the day for the programme. He gave brief overview about what are the nature inspired algorithms?

Later programme was formally inaugurated by the worthy Principal coordinator, Prof. Madhusudan, HOD EED of DTU, Delhi and delivered an inaugural address. Dr. Dheeraj Joshi, Dr. Bharat Bhusan, Course Coordinator, given brief overview about the programme and day wise schedule along with concern speakers.

Day 1 : 13 Jul 15

Session started with the lecture of Prof. V. K. Minocha on Relevance and application of ANN & GA. He explained in detail about the Limitations of Classical Optimizers, NN and Evolutionary Computing, Need to generate Artificial Intelligence System - AIS, Back Propagation & Feedforward Algorithms and difference between Artificial Neural Network and Genetic Algorithm.

Prof. Jagdish Chand Bansal, South Asian University, New Delhi gave a talk on Biogeography Based Optimization Techniques. He Defined Computational Intelligence and explained Why it is important to study CI? What is the difficulty in the study of CI? He detailed working of Biogeography Based Optimization Technique, Mathematical model of BBO, Operators of BBO, Some Recent Advances in BBO and BBO Examples.

Dr. Asha Rani, Associate Professor, I & C Deptt.,NSIT, New Delhi gave her lecture on Modeling and Control of Distillation Process using Intelligent Techniques. She gave an overview of research methodology, Schematic Diagram of a typical Distillation Column, LM based ANN, Least Mean Square Algorithm and the use of LM based ANN in typical Distillation Column.

DAY 2 : 14 Jul 15

Dr. Dheeraj Joshi, Associate Prof. DTU, Delhi on Genetic Algorithm Technique in his lecture mentioned about Darwin’s theory of Evolution Survival of the Fittest, What is an Optimization? What do we optimize? Components of a GA, Genetic operators and Computational problems with solution of GA.

Particle Swarm Optimization and its application was explained by Prof. S. K. Aggarwal, Professor and Head (EED), M. M. University, Mullana. During his lecture he covered Key Elements of Computational Intelligence, Perspective of Kennedy and Eberhart, PSO and Optimization, Comparison between GA and PSO, How the PSO algorithm works? Applications of PSO and Benchmark Optimization Problem using PSO.

Hand on Training was organised on Particle Swarm Optimization and Genetic Algorith using MATLAB in afternoon session coordinated by Dr. Bharat Bhusan, Dr, Dheeraj Joshi and Dr. S. K. Aggarwal.

Day 3 : 15 Jul 15

Dr. Bharat Bhushan, Associate Professor, Delhi Technolgical University, started his talk on Bacterial Foraging Optimization Algorithm. He detailed about Classical versus Intelligent control, Foraging Theory, Bacterial Foraging E.Coli, Bacterial Motile behaviour, Elimination and Dispersal Events in BFOA, E .Coli bacterial swarm foraging for optimization. He also explained a Pseudo code for BFOA with example during his talk.

Soft Computing Applications to Power System Issues was explained by Dr. Sukumar Mishra, Electrical Engineering Department, IIT, DELHI during his talk. He gave overview of Soft computing, Constituents of SC, Advantages of SC. He told that Mathematical discipline which is concerned with finding the maxima and minima of functions, possibly subject to constraints is called optimization. He also mention that why it necessary of using Soft Computing optimization techniques over classical method? Even though classical optimization techniques gives more accurate result as compared to Soft Computing optimization techniques.

Practical session was conducted under the guidance of Dr. Bharat Bhusan and Dr. Dheeraj Joshi in afternoon session. Dr. Dheeraj Joshi explained about Simulation annealing and all participants performed practical on Simulation annealing using MATLAB code. Dr. Bharat Bhusan taught of Bacterial Foraging Optimization algorithms and its pseudo code on MATLAB. All the participants had hands on experience on Annealing and BFOA algorithm which was verified and guided by course coordinators.

Day 4 : 16 Jul 15

Session was started with the talk of Dr. Vivek Shrivastava, Associate Professor, Department of Electrical Engineering, Rajasthan Technical University, Kota on Ant Colony Optimization. he showed several examples on Ant Colony Optimization such as traveling - salesman problem and Double Bridge Experiment. His talk was specially emphasise on how ant colony optimization technique works? What are the application area of ACO? How to implement on real engineering problem. He also explained pseudo code of ACO algorithm for traveling-salesman problem and Double Bridge Experiment.

Particle Swarm Optimization: An Interactive Introduction was explained by Dr. Anupam Yadav, Asst. Professsor, National Institute of Technology, Uttarakhand. His talk was started with an overview of Population Based Search Algorithm and Natural Inspiration for PSO. He told that Particle Swarm optimization (PSO) is a population based nature inspired search technique and it was developed by James Kennedy (social psychologist) and Russell Eberhart (Electrical Engineer). He outlined his talk on Abstract formulation of PSO, Formal formulation of PSO, PSO Algorithm, Logical flow of PSO algorithm and step by step solution of PSO through basic example.

Afternoon session was started by Prof. Parmod Kumar, Dean - IRD, MAIT on Grey Relational Decision Optimization. His talk includes Definition of Grey System, Grey Analysis, Aim of Grey System Theory, Grey Relational Decision Optimization algorithm and its step by step solution for given problem and Fuzzy considerations for algorithm. He mentioned that in the inference procedure, the real value of each objective function is first calculated to get the firing strength in fuzzy if – then rules.

Day 5 : 17 Jul 15

The session was started with the talk of Dr. Rajneesh Sharma, Associate Professor, NSIT on Lyapunov Theory based Hybrid Fuzzy - Neural Reinforcement Learning Controllers for non linear System. His talk was basically focused Reinforcement Learning Algorithms, Markov Decision Process, General Controller structure : MDP setting, Fuzzy Q Learning, Lyapunov’s Direct Method, Lyapunov constrained neural network based RL control and comparative analysis of Hybrid Fuzzy Lyapunov based RL control for Inverted Pendulum.

Philosophy to Implementation of Artificial Bee Colony (ABC) and Spider Monkey Optimization was highlighted by Prof. Jagdish Chand Bansal. Later, he described Necessary and sufficient properties for swarm intelligence, behaviour of honey bee swarm, Fission - Fusion Social Structure of Spider Monkey, Basic Flow of SMO and Detailed Pseudo Code and C Code of ABC. He also discussed Step by Step Procedure of ABC for a given optimization problemand result was compared with Genetic Algorithm and PSO.

The valedictory function was organised in post lunch session followed by certificate distribution to the participants. The program was concluded by the Principal coordinator, Prof. Madhusudan and vote of thanks by course coordinator Ms. Garima.

 
   
 

 

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