@inproceedings{48879,
  abstract     = {{Evolving diverse sets of high quality solutions has gained increasing interest in the evolutionary computation literature in recent years. With this paper, we contribute to this area of research by examining evolutionary diversity optimisation approaches for the classical Traveling Salesperson Problem (TSP). We study the impact of using different diversity measures for a given set of tours and the ability of evolutionary algorithms to obtain a diverse set of high quality solutions when adopting these measures. Our studies show that a large variety of diverse high quality tours can be achieved by using our approaches. Furthermore, we compare our approaches in terms of theoretical properties and the final set of tours obtained by the evolutionary diversity optimisation algorithm.}},
  author       = {{Do, Anh Viet and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference}},
  isbn         = {{978-1-4503-7128-5}},
  keywords     = {{diversity maximisation, evolutionary algorithms, travelling salesperson problem}},
  pages        = {{681–689}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{Evolving Diverse Sets of Tours for the Travelling Salesperson Problem}}},
  doi          = {{10.1145/3377930.3389844}},
  year         = {{2020}},
}