Evolutionary Computation for Single and Multi-Objective Optimization
Evolutionary computation (EC) is a sub-field of computational intelligence that use ideas and get inspiration from natural evolution. It is based on Darwin’s principle of evolution where the population of individuals iteratively performs search and optimization. EC techniques can be applied to optimization, learning, design and many more. This course will concentrate on the concepts, algorithms, hand-calculations, graphical examples, and applications of EC techniques. Topics will be covered include binary and real-coded genetic algorithms, differential evolution, particle swarm optimization, multi-objective optimization and evolutionary algorithms, and statistical assessment. Students will be taught how these approaches identify and exploit biological processes in nature, allowing a wide range of applications to be solved in industry and business. Students will have the opportunity to build and experiment with several different types of EC techniques through-out the course.
INTENDED AUDIENCE :Final and Pre-final year UG students, PG Students and Candidates from IndustriesPREREQUISITES : Elementary Mathematics and ProgrammingINDUSTRIES SUPPORT :All R&D industries that involve design and optimization of product and system