A multi-objective evolutionary algorithm based on double chains(DCMOEA) is proposed, which is characterized with populated individuals based on double chains, no external archive is needed, and the ?? dominance mechanism is adopted for preserving population diversity. The DCMOEA is compared with MOEA/D, NSGA-II, SPEA2 and PAES simultaneously on the platform employing four 2-objective ZDT test functions and four 3-objective DTLZ instances from three aspects including convergence, spacing and maximum spread. Experimental results show that the DCMOEA has the best comprehensive performance among five multi-objective evolutionary algorithms, and is a promising multi-objective evolutionary algorithm.