Although there are studies on optimizing organic Rankine cycles (ORCs) through individual components, in this study, for the first time, both evaporator and turbine designs are included in a multiobjective optimization. Twenty-eight working fluids are used to find optimum cycle parameters for three source temperatures (90, 120, and 150 °C). A mean-line radial inflow turbine model is used. Nondominated Sorting Genetic Algorithm II is utilized to minimize total evaporator area per net power output and maximize performance factor simultaneously. The technique for Order Preference by Similarity to Ideal Situation (TOPSIS) procedure is followed to obtain ideal solutions. A group of working fluids with highest net power output is determined for each heat source temperature. Optimized geometric parameters of the evaporator vary in a narrow range independent of the working fluid and the source temperature, but evaporator PPTD and degree of superheating depend on the working fluid. The specific speed, the pressure ratio through the turbine, and the nozzle inlet-to-outlet radius ratio do not change significantly with cycle conditions.