This research presents a multi-objective optimization analysis of an existing house to evaluate the as built performance and inform future design decisions. Optimization was performed by coupling a genetic algorithm to a building simulation engine, and varying passive conservation parameters to minimize life cycle cost and improve performance simultaneously. A case study house was used as the optimization reference building, where the building energy model was calibrated against utility bills, indoor air temperature, and spot measurements to replicate in-situ behavior. The results identified 42 more cost effective, Pareto optimal, design solutions for the case study house. Optimal results were largely influenced by upfront construction costs, especially for glazing packages. The study also showed that energy savings of 33% relative to local building code minimum requirements were justified economically at the point of minimum life cycle cost via passive energy efficiency measures alone. (C) 2016 Elsevier B.V. All rights reserved.