Multivariate optimization of neighborhood scale problems for economic, environmental, and social sustainability

Abstract

This thesis begins by arguing that the architectural profession has fallen out of balance. I contend that the series of objectives which compete for the architect’s attention have been gradually subsumed by economic concerns. As a means of empirically seeking to restore a balance, a method is proposed for quantitatively determining the trade-offs between the social, economic, and environmental sustainability of an architectural problem. The method is tested on a neighborhood-scale mega-development. This scale of built environment intervention falls between the building scale work of architects and the city scale of urban designers and geographers.

The selected design intervention is in Chicago, Illinois with variables including the number of buildings, their use, and the height of each type of building. Solutions are optimized for Social, Economic, and/or Environmentally sustainability outcomes using a single-objective genomic algorithm. A multi-objective genomic algorithm is then utilized to evaluate all three sustainability objectives simultaneously. Solutions to the chosen problem are proposed and contextualized within the “restoring balance” framework discussed above. The outcomes appear to show that such a process can be efficacious in quantitatively balancing the sustainability based trade-offs implicit to the design process.