Applying global and local SA in identification of variables importance with the use of multi-objective optimization

Methods for global and local Sensitivity analysis are designed to identify and rank variables importance for each design objective and constraint. This paper investigates the application of local sensitivity analysis to a set of Pareto optimum solutions resulting from the multi-objective minimization of energy use and capital cost, with occupant thermal comfort acting as a constraint. It is concluded that the local sensitivities vary along the trade-off and that these sensitivities are different to the global sensitivities. Different sensitivity behaviour is also observed both along the Pareto trade-off and between variables.