Optimum design of low-cost housing in developing countries using nonsmooth simulation-based optimization

An optimum design of Low-cost housing (LCH) offers low-income urban inhabitants great opportunities to obtain a shelter at affordable price and acceptable indoor thermal conditions. In the present study, the design and operation of a low cost dwelling were numerically optimized using simulation-based approach in which a dynamic building simulation program (EnergyPlus) was coupled with the optimization engine (GenOpt). Three multi-objective cost functions which include construction cost, indoor thermal comfort and 50-year operating cost were applied for naturally ventilated (NV) and air-conditioned (AC) buildings. Optimization problem which consists of 18 building parameters combined with 6 ventilation strategies was examined by two population-based optimization algorithms (Particle Swarm optimization and Hybrid algorithm) to find optimum combinations among these variables. The results show that the design requirements of NV and AC dwellings are not quite similar, and in a few categories, even contradictory. Optimum design corresponding to each cost function was outlined. Results of this paper also show great potential of optimization in comfort improvement, energy saving, life cycle cost, up to 40%.