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With the chip multi-processor (CMP) being more and more widespread used in the laptop, desktop and data center area, the power-performance scheduling issues are becoming challenges to the researchers. In this paper, we propose a multi-objective fuzzy genetic algorithm to optimize the energy saving scheduling tasks on heterogeneous CMP system. According to the characteristic of heterogeneous CMP system, we present a novel encoding and decoding scheme of genetic algorithm, improve the crossover operator and the mutation operator. Based on that, we improve the genetic algorithm architecture by using the relative fuzzy membership grade fitness and the elitist strategy. Simulation results demonstrate that using our algorithm can save both the execution time and system energy cost at the same time.