Quality Diversity Approaches for Time-Use Optimisation to Improve Health Outcomes

Adel Nikfarjam, Ty Stanford, Aneta Neumann, Dorothea Dumuid, Frank Neumann

Abstract: How people spend their finite time budget of 24 hours on daily activities is linked to their wellbeing. Yet, how to best allocate time to optimise multi-dimensional wellbeing (physical, mental and cognitive) remains unknown. Here, we utilise a number of (objective) functions derived using compositional data analysis and a large child cohort (n > 1000), to predict how time allocation is associated with wellbeing outcomes such as body mass index, life satisfaction, and cognition. We develop and advocate joint cumulative distribution function constraints to ensure the feasible solutions do not extrapolate the sampled data for which the objective function is derived from. Moreover, we incorporate quality diversity (QD) approaches to study these objective functions. We define two types of behavioural spaces (BSs), one based on the activities, called the variable-based BS, and the other based on objectives. The variable-based BS aids in studying solution space and generating a set of high-quality solutions with different variable values, while the objective-based BS is beneficial in diversifying the objective values for a number of objective functions while optimising another. We also demonstrate a web application, Time allocation optimiser, providing personalised, optimised time-use plans.