Spacecraft Multiple-Impulse Trajectory Optimization Using Differential Evolution Algorithm with Combined Mutation Strategies and Boundary-Handling Schemes

Abstract

Since most spacecraft multiple-impulse trajectory optimization problems are complex multimodal problems with boundary constraint, finding the global optimal solution based on the traditional differential evolution (DE) algorithms becomes so difficult due to the deception of many local optima and the probable existence of a bias towards suboptimal solution. In order to overcome this issue and enhance the global searching ability, an improved DE algorithm with combined mutation strategies and boundary-handling schemes is proposed. In the first stage, multiple mutation strategies are utilized, and each strategy creates a mutant vector. In the second stage, multiple boundary-handling schemes are used to simultaneously address the same infeasible trial vector. Two typical spacecraft multiple-impulse trajectory optimization problems are studied and optimized using the proposed DE method. The experimental results demonstrate that the proposed DE method efficiently overcomes the problem created by the convergence to a local optimum and obtains the global optimum with a higher reliability and convergence rate compared with some other popular evolutionary methods.

Hygro-Thermally Curvature-Stable Free-Layer Composite Laminates with Extension-Twist Coupling

“…strength are included, and the optimization of HTCS free-layer A S B t D S laminates is achieved algorithm used for optimization, which called Differential Evolution_Combined Mutation Stra and Boundary Handling Scheme (DE_CMSBHS), is an improved Differential Evolution algorith efficient global optimization algorithm. Combined with the ability to handle constraints of p function [10,11], this algorithm can solve the nonlinear constrained problem of optimi effectively [12].…”

EP_DE II: A significant algorithm to search the optimal solution for global optimization of multi-gravity assist trajectory

“…While in the later stage, its instability may affect the efficiency of EP_DE. Zhu et al 8 introduced the method of combining different mutation strategies, which makes full use of the advantages of various MS. Results of experiment 3 show that efficiency of EP_DE II is affected by DE, because its former process is composed by the computation procedure of DE algorithm.…”

“…Each algorithm proposed can be tested by GTOP to show the efficiency of the method. [6][7][8] Between 2005 and 2010, many researchers had published their achievements obtained by a wide range of methods on the website of ESA. These excellent algorithms include monotonic basin hopping (MBH), differential evolution (DE), particle swarm optimizer (PSO), and so on.…”

Optimization of Hybrid Laminates with Extension-Shear Coupling

“…The DE_CMSBHS algorithm is an efficient global optimization algorithm, which has the characteristics of simple structure, easy realization, fast convergence, and strong robustness, and can effectively solve the single-objective optimization problems such as integer problems, real problems, and mixed integer-real problems [12]. The single-objective nonlinear optimization problems are able to be solved well by combining the penalty function's ability to handle constraints with the optimal performance of DE_CMSBHS algorithm [13,14].…”