  Diversification in a set of solutions has become a hot research topic in the
evolutionary computation community. It has been proven beneficial for
optimisation problems in several ways, such as computing a diverse set of
high-quality solutions and obtaining robustness against imperfect modeling. For
the first time in the literature, we adapt the evolutionary diversity
optimisation for a real-world combinatorial problem, namely patient admission
scheduling. We introduce an evolutionary algorithm to achieve structural
diversity in a set of solutions subjected to the quality of each solution. We
also introduce a mutation operator biased towards diversity maximisation.
Finally, we demonstrate the importance of diversity for the aforementioned
problem through a simulation.
