National Weather Center Colloquium
CULTURAL-BASED PARTICLE SWARM OPTIMIZATION
FOR MULTIOBJECTIVE OPTIMIZATION
Gary G. Yen
Oklahoma State University
School of Electrical and Computer Engineering
25 April 2012, 3:00 PM
National Weather Center, Room 1350
120 David L. Boren Blvd.
University of Oklahoma
Evolutionary computation is the study of biologically motivated computational paradigms which exert novel ideas and inspiration from natural evolution and adaptation. The applications of population-based heuristics in solving multiobjective optimization problems have been receiving a growing attention. To search for a family of Pareto optimal solutions based on nature-inspiring problem solving paradigms, Evolutionary Multiobjective Optimization Algorithms have been successfully exploited to solve optimization problems in which the fitness measures and even constraints are uncertain and changed over time.
In this talk, I will review the cultural-based particle swarm optimization (PSO) to solve these problems with real-world complications. A cultural framework from sociology is incorporated to manage the required data/information from the PSO into belief space. The archived information is exploited to detect the changes in the environment and assists response to the change and constraints through a diversity based repulsion among particles and migration among swarms in the population space.
In addition, a plan to tackle weather and meteorological forecast model based on evolutionary multiobjective optimization will be suggested, given our limited knowledge, to improve dynamics modeling and forecasting accuracy. The focus of the talk will be placed on this emerging technology and its potential to address one of the most challenging problems we face today, reliable weather prediction.