Housing Arrangements in Pursuit of Maximum GFA Under CO2 Emission Constraint

This paper attempts to develop a management instrument for housing arrangements under given constraints regarding household annual CO2 emissions (HACO2). HACO2 was defined as the sum of the life cycle CO2 emission from house construction and operation (LCCO2) and the CO2 emission from commuting (CTCO2). Under such an instrument rule, genetic algorithm (GA) was used to find a housing arrangement scheme in pursuit of the maximum average gross floor area (GFA) in an urban area. Simulation tests were performed and compared on three traffic modes: public-mode, self-mode, and mixed-mode. The results indicated that, 1) the closer the house was to the workplace (the nucleus of the city), the larger the GFA would be; 2) different traffic modes might lead to different patterns of housing arrangement; and 3) the self-mode had high-energy demand resulting in the lowest evaluation value, and was the least efficient in obtaining better living conditions under the constraints.