Evolutionary Many-objective Optimization of Vehicle Dynamics”

Yoachu Jin, Westlake University, China ABSTRACT: This talk starts with a brief introduction to optimization problems having a large number of conflicting objectives, known as many-objective optimization problems. Then, it introduces recently proposed evolutionary algorithms that adapt the reference vectors to handle irregular and computationally expensive many-objective optimization problems. This is following by two real-world examples of many-objective optimization problems, i.e., design of a controller of hybrid electric vehicles consisting of seven objectives and optimization of vehicle dynamics handing 20 objectives.