Multi-objective Optimization with Proper Orthogonal Decomposition and Gaussian Predictive Distribution
Multi-objective Optimization with Proper Orthogonal Decomposition and Gaussian Predictive Distribution
Hou Liqiang, Zhao Gang, Yang Yue and Hou Zhaohui
Hou Liqiang, Zhao Gang, Yang Yue and Hou Zhaohui
State Key Laboratory of Astronautic Dynamics,Xi'an Satellite Control Center, Xi'an, China, China
State Key Laboratory of Astronautic Dynamics,Xi'an Satellite Control Center, Xi'an, China, China
School of Software Engineering, Xi'an Jiaotong Univer
State Key Laboratory of Astronautic Dynamics,Xi'an Satellite Control Center, Xi'an, China, China
State Key Laboratory of Astronautic Dynamics,Xi'an Satellite Control Center, Xi'an, China, China
School of Software Engineering, Xi'an Jiaotong Univer
A numerical study of multi-objective optimization
with Proper Orthogonal Decomposition (POD) and Gaussian
predictive distribution on the well known ZDT and DLZT benchmark
set, is presented and discussed. Based on the algorithm,
design optimization of the Global Trajectory Optimization Problems
(GTOP) database based on trajectory models of real-world
interplanetary space mission, Cassini is presented. The trajectory
models are formulated as nonlinear optimization problems and
are known to be difficult to solve. In this contribution, for part
of the standard ZDT and DTLZ series problems, the proposed
algorithm is able to solve these benchmarks to their optimal
solutions within 20 generations.
