Crossover-First Differential Evolution: A Comprehensive Post-Hoc Analysis

Explore a new evolutionary optimization approach using Crossover-First Differential Evolution. Implementation details explained clearly with a comprehensive post-hoc statistical analysis to support the algorithm. Sample code is also provided for a quick implementation.

Jason Teo is an associate professor in computer science at the Faculty of Computing and Informatics, Universiti Malaysia Sabah. He received his doctorate in information technology from the University of New South Wales, Australia, researching Pareto artificial evolution of virtual legged organisms. He has over 200 publications in the areas of Differential Evolution, neuroinformatics, evolutionary computation, artificial life and evolutionary robotics. His current research focuses on the applications of bio-inspired computing to expensive and large-scale optimization problems, neuroinformatics, robotics and video games. He is a senior member of IEEE, professional member of ACM and program evaluator for ABET.