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%.