Global optimization of interplanetary low-thrust trajectory based on differential evolution

A novel global optimization approach for interplanetary low-thrust trajectory based on modified differential evolution is proposed. First, the trial vector regeneration strategy and constraint selection criteria are introduced into differential evolution process, which can keep the optimization variables and trajectory constraints from boundary violation. Then, in order to improve the convergence efficiency of differential evolution close to the global optimum, a new mutation operation with best individual information and an assistant local optimization strategy are proposed. Taking optimal-fuel low-thrust transfer from earth to mercury as an example, the modified differential evolution algorithm (MDEA) is validated. The simulation results demonstrate that the proposed algorithm is effective to find the global optimal transfer trajectory, and have higher reliability and better convergence ability comparing to sequential quadratic programming and genetic algorithm.