Constrained, mixed-integer and multi-objective optimisation of building designs by NSGA-II with fitness approximation
A surrogate based on radial basis function networks is adapted for mixed-type variables, multiple objectives and constraints and integrated into NSGA-II. A deterministic method to include infeasible solutions in the population is proposed. Variants of NSGA-II including these changes are applied to a typical building optimisation problem, with improvements in solution quality and convergence speed. Analysis of the constraint handling and fitness landscape of the problem is also conducted.
multi-objective nsga-ii surrogate constraints simulation-based optimisation