Nested multi- and many-objective optimisation of team track pursuit cycling

Abstract

Team pursuit track cycling is an elite sport that is part of the Summer Olympics. Teams race against each other on special tracks called velodromes. In this article, we create racing strategies that allow the team to complete the race in as little time as possible. In addition to the traditional minimization of the race times, we consider the amount of energy that the riders have left at the end of the race. For the team coach this extension can have the benefit that a diverse set of trade-off strategies can be considered. For the optimization approach, the added diversity can help to get over local optima. To solve this problem, we apply different state-of-the-art algorithms with problem-specific variation operators. It turns out that nesting algorithms is beneficial for achieving fast strategies reliably.