A multi-objective strength Pareto chaotic differential evolution algorithm(SPCDE) is proposed. Firstly, the chaotic
initialization based on the Tent map is adopted to initialize the population. A truncation crowding operation based on a
uniform crowding mechanism and a chaotic substitution operation are introduced to the environmental selection operation of
the population. Then, the differential mutation operation is operated based on a differential mutation strategy with changing
scaling factor, and the mutation individuals are obtained by computing the dominance relation. Finally, the evolutionary
selection operation is operated and the offspring individuals are obtained by the dominance relation computation and the
environmental selection operation. The operations above mentioned not only enhance the convergence performance of the
proposed algorithm, but also maintain the uniformity of the Pareto optimal solution. Numerical experiment results show the
effectiveness of the proposed algorithm.