摘要： The aim of the present study is to solve multiobjective optimization (MO) of an off-grid hybrid power generation system including photovoltaic (PV) and diesel generator by multiobjective version of a recently developed metaheuristic approach named crow search algorithm (CSA). For this goal, the objective functions are regarded as net present cost (NPC) and system reliability defined by loss of power supply probability (LPSP) index. In the optimization problem, operating limitations of diesel generator and uncertainties of solar radiation and load demand are considered. To solve this problem, a multiobjective CSA (MO-CSA) is developed and the obtained results are compared with the results of nondominated sorting genetic algorithm II (NSGA-II). On the case study, simulation results reveals that when diesel generator ramp rate is 100%, at LPSP = 0, MO-CSA reaches to 54.8 kW and 172.8 m2 for rated power of diesel generator and PV surface area (corresponding cost is 3.7219 × 105 $), while the values found by NSGA-II are 55 kW and 86.04 m2 (corresponding cost is 3.7345 × 105 $). Based on the results, it can be drawn that (1) MO-CSA finds more promising results than NSGA-II, (2) Combination of PV and diesel generator leads to having a cost-effective and reliable power generation system, and (3) by considering the solar radiation and load uncertainties, the system cost increases.