This paper presents an innovative approach to assess the impact of land use mix and its density on various energy and environmental performance criteria, and to select optimal design solutions to meet the specific environmental criteria. Land use is defined using five neighborhood design variables, relating to the composition of different residential building types, their density, and the ratio of commercial to residential floor area. The studied energy and environmental impact include: energy consumption, photovoltaic (PV) energy generation, Waste to Energy potential (WtE) and Greenhouse Gas (GHG) emissions. Integrated mixture and full factorial based crossed statistical design is employed to develop correlations relating design variables to energy and environmental response variables. In addition, a genetic algorithm (GA) based multi-objective optimization is carried out to simultaneously optimize the five performance parameters. This is followed by the application of a selection procedure based on decision making score (DMS) to select best combinations associated with designated priorities. The main results indicate that to optimize non-fossil fuel based energy generation (PV and WtE), a higher percentage of apartment buildings with maximum commercial to residential ratio and density is recommended. To achieve a balance between energy consumption, GHG emissions and energy generation potential, a neighborhood should contain an optimal ratio of commercial to residential buildings of about 0.25. In addition, in designing a neighborhood for specific population density, considering the impact of population size along the number of residential units, allows to achieve more flexibility and variations, in the selection of residential building types.