For the abundance speciality,blind source separation algorithm is d ifficult to be used for the hyperspectral unmixing directly.At the same time,traditional gradient algo rithm is easy to fall into the local extremum when it optimize the objective function in unmixing process.For this purpose,we propose a hyperspectral unmixing algorithm based on multi-objective bat o ptimization algorithm in this paper.This algorithm makes the abundance non-negative constraint and abun dance sum-to-one constraint as objective functions for unmixing.Thus,unmixing problem is tr ansformed into a multi-objective function optimization problem.At the same time,we introduce the multi-objective bat optimization algorithm to optimize the objective function,thus realize the hyperspe ctral unmixing.The experimental results show that the hyperspectral unmixing algorithm based on multi objective bat optimization can solve the ab ove problems effectively,in addition,when the signal-to-noise ratio,purity o f pixel and the number of pixels in image are changed, the changes of spectral angel distance and root me an square error are observed.We can see that compared with other unmixing algorithms,the new algorithm has higher decompositi on accuracy,and its anti-noise interference ability is strong.It can also be used at mixed pixel de composition with very low purity.