Simulation models, such as agent-based or microsimulation models capturing urban contexts, increasingly draw on spatially explicit, attribute-rich synthetic population datasets as real-world data inputs. Despite their growing relevance, the creation of such datasets via simulated annealing still faces significant limitations. Addressing key limitations, we present the open-source software package Combinatorial Optimisation for Microdata Population Assembly and Spatial Synthesis (COMPASS). The algorithm implemented in COMPASS enables; aggregate-level representativeness at different levels of counts (e.g., households and individuals); the processing of nested input data (e.g., retaining survey household and kinship structures); and systematic monitoring of uncertainty arising at creation stage. We provide COMPASS as a compiled multi-platform software package, suitable for reproducible workflows via R and Python. This paper introduces COMPASS and illustrates one potential workflow using open access data created to reflect an artificial population – transferable to many national contexts.