Hybrid Approach to Optimize a Rendezvous Phasing Strategy
Ya-Zhong Luo, Haiyang Li, Guo-Jin Tang · Journal of Guidance Control and Dynamics · 2006
DOI: 10.2514/1.20232 The design of a rendezvous phasing strategy can be formulated as a mixed integer nonlinear programming problem. A new hybrid approach combining a genetic algorithm with Newton’s method is proposed for solving this problem. An integer-coded genetic algorithm is used to handle the discrete design variables, whereas Newton’s method is applied to handle the continuous design variables. Three improvements are imposed on the hybrid approach to make it more efficient and robust. The first improvement is not to impose the exact analysis on the explicitly constraint-violated design variables. The second is to use a memory database to record the previously completed analysis, and the third is to renew the initial guess to Newton’s method by the nearest one in the memory database. A two-day rendezvous phasing problem is used as an example. Results show that our hybrid approach is effective, efficient, and can find multiple solutions in a single run.