Applying desirability functions to preference modelling in low-energy building design optimization
Building performance optimization is a valuable aid to
design decision-making. Most existing research takes an
‘a posteriori’ approach, where stakeholder preferences are
considered after deriving optimised results. Whilst this
approach yields technically optimal solutions, it
overlooks sub-optimal solutions that still satisfy
stakeholder preferences. This research develops a
technique to incorporate preferences into optimization by
applying a “desirability function” to each criterion for
multiple stakeholders. The approach enables the tradeoffs between decision-makers to be visualised as a Pareto
frontier and aids “democratic” decision-making. Hence,
incorporating preferences in advance of optimization may
increase the likelihood of finding a desirable solution.