A benchmarking framework for simulation-based optimization of environmental models

The proposed guidelines were used to investigate problems involving sorptive landfill liners for containing and treating hazardous waste. Two solution approaches were applied to these types of problems for the first time - a pre-emptive (i.e. terminating simulations early when appropriate) particle swarm optimizer (PSO), and a hybrid discrete variant of the dynamically dimensioned search algorithm (HD-DDS). Model pre-emption yielded computational savings of up to 70% relative to non-pre-emptive counterparts. Furthermore, HD-DDS often identified globally optimal designs while incurring minimal computational expense, relative to alternative algorithms. Results also highlight the usefulness of organizing decision variables in terms of cost values rather than grouping by material type.