Nature-inspired Optimization is an interdisciplinary field and a branch of artificial intelligence that employs processes, which is involved in evolution of living beings, biology and nature for solving complex problems. Artificial Intelligence covers higher level processes like problem solving, reasoning, making inferences in abstract and virtual worlds that consist of precisely defined states and operations in closed systems unlike real world. During the last decade, due to the convergence of Bio, Nano and Information Technology, an appreciable amount of research has been done on sensors and actuators, which leads to the design of many autonomous agents and robots and subsequently the development of Multi Agent Systems (MAS) for real world applications. Nature-inspired Optimization can be applied to a variety of problems, ranging from engineering and scientific research to manufacturing industry and transportation and communication business as they provide robust and flexible solutions along with learning and adaptability as compared to traditional optimization techniques. It can be applied to solve optimization issues in any domain and may be unified as Nature-inspired computing and optimization (NICO). While studying the nature, researchers found a number of cases from ant, bee, flock of birds, frog, cuckoo, firefly, bat, crocodile etc., which can be modelled for real-world problem. Looking at the emergence of bio, info and nano technology it can be quoted confidently that the field of the nature-inspired computing and optimization can solve many complex real world problems. The seminar talk shall cover few of the methods of nature inspired computing and optimization. They are as follows:
•Ant Colony Optimization (ACO)
•Bee Colony Optimization
•Bacterial Foraging Optimization
•Particle Swarm Optimization
•Cuckoo search Optimization
•Firefly algorithm Optimization
•Bat algorithm Optimization
Dr. Srikanta Patnaik is a Professor in the Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, India. He has received his Ph. D. (Engineering) on Computational Intelligence from Jadavpur University, India in 1999 and supervised 15 Ph. D. theses and more than 50 M.S. theses in the area of Computational Intelligence, Soft Computing Applications and Re-Engineering. Dr. Patnaik has published around 100 research papers in international journals and conference proceedings. He is author of 2 text books and edited 15 books and few invited book chapters, published by leading international publisher like Springer-Verlag, Kluwer Academic, etc.. Dr. Patnaik was the Principal Investigator of AICTE sponsored TAPTEC project “Building Cognition for Intelligent Robot” and UGC sponsored Major Research Project “Machine Learning and Perception using Cognition Methods”. He is the Editors-in-Chief of International Journal of Information and Communication Technology and International Journal of Computational Vision and Robotics published from Inderscience Publishing House, England and also Editors-in-chief of Book Series on “Modeling and Optimization in Science and Technology” published from Springer, Germany.