Tracker 20-Nature Inspired Optimization Algorithms and their Applications

Nature inspired algorithms (NIA) are techniques mimicking the different natural phenomena like the concept of evolution and the behavioral pattern displayed by various species. NIA serve as an attractive alternative for solving complex and intricate problems which cannot be solved by the usual techniques. Some popular NIA include Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) etc. These methods have been successfully applied to a wide range of benchmark and real-world application problems. This special session seeks to bring forward and highlight the latest developments in this promising research area by bringing together researchers and practitioners of diverse fields. Authors are invited to submit their original and unpublished work to this Special Session. Topics of interest include, but are not limited to:

Theory of Nature inspired optimization algorithms
Parameter settings in Nature inspired optimization algorithms
Adaptive Nature inspired optimization algorithms
Multi-objective Nature inspired optimization algorithms
Nature inspired optimization algorithms for noisy problems
Nature inspired optimization algorithms for constrained optimization
Hybridization of Nature inspired optimization algorithms with local search and other soft computing approaches
Comparison of  Nature inspired optimization algorithms with other Techniques
Parallel implementation
Real world/ novel applications
New concepts for Nature inspired optimization algorithms
 
Track Chairs:
Professor Kusum Deep, Mathematics Department, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India.
Mail: kusumfma@iitr.ernet.in
Dr. Millie Pant, Assistant Professor, Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India.
Mail: millifpt@iitr.ernet.in