Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation

• URL: http://arxiv.org/abs/2207.14112v1
• Date: Thu, 28 Jul 2022 14:26:45 GMT
• Title: Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation
• Authors: Adel Nikfarjam, Amirhossein Moosavi, Aneta Neumann, and Frank Neumann
• Abstract summary: We adapt the evolutionary diversity optimisation for a real-world 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.
• Score: 10.609857097723266
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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