Multi-satellite imaging task planning algorithms based on gene expression programming

doi:10.7523/j.issn.2095-6134.2020.04.013

Abstract

Abstract: The constraint-satisfaction model is established by analyzing the constraints of multi-satellite imaging mission planning for regional targets, and the mathematical complexity of the model is analyzed. In order to improve the weak global searching ability of the genetic algorithm in multi-satellite imaging mission planning, the gene expression programming (GEP) is first proposed in this work to solve the problem. In the process of algorithm implementation, the inverted genetic operator is designed to enhance the search ability for the optimal solution, and the repository is introduced to preserve elite individuals in the iteration process. The results show that the gene expression programming (GEP) is effective and reasonable in solving multi-satellite imaging planning problems and greatly improves the accuracy of the solution.

Key words: gene expression programming(GEP), regional target, multi-satellite imaging planning, genetic algorithm

CLC Number:

P236
TP212

MING Weipeng, MA Guangbin, ZHANG Wenyi. Multi-satellite imaging task planning algorithms based on gene expression programming[J]. , 2020, 37(4): 532-538.

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