The precision and power consumption of pipelined FFT processors are highly affected by the wordlengths in fixed-point application systems. Due to nonconvex space, wordlength optimization under multiple competing objectives is a complex, time-consuming task. This paper proposes a new approach to solving the multi-objective evolutionary optimization design of pipelined FFT processors for wireless OFDM receivers. In our new approach, the number of design variables can be significantly reduced. We also fully investigate how the internal wordlength configuration affects the precision and power consumption of the FFT by setting the wordlengths of input and FFT coefficients to be 12 and 16 bits in fixed-point number type. A new system-level model for representing power consumption of the pipelined FFT is also developed and utilized in this paper. Finally, simulation results are provided to validate the effectiveness of applying the nondominated sorting genetic algorithm to the multi-objective evolutionary design of a 1024-point pipelined FFT processor for wireless OFDM receivers.