Integrated scheduling problem for earth observation satellites based on three modeling frameworks: an adaptive bi-objective memetic algorithm

• Published in: Memetic computing Vol. 13; no. 2; pp. 203 - 226
• Main Authors: Chang, Zhongxiang, Zhou, Zhongbao, Xing, Lining, Yao, Feng
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021; Springer Nature B.V
• Subjects: Adaptive algorithms; Algorithms; Applications of Mathematics; Artificial Intelligence; Bioinformatics; Complex Systems; Control; Data transmission; Earth observations (from space); Engineering; Genetic algorithms; Mathematical and Computational Engineering; Mechatronics; Operators; Optimization; Regular Research Paper; Robotics; Satellite imagery; Satellite observation; Satellites; Scheduling; Search algorithms; Sorting algorithms; Data transmission; Memetic algorithm; Bi-objective optimization; Scheduling; Data acquisition; Integrated scheduling problem
• ISSN: 1865-9284; 1865-9292
• DOI: 10.1007/s12293-021-00333-w

With the number of on-orbit earth observation satellites (EOSs) increases, satellite image data downlink scheduling problem is becoming the bottleneck for restricting EOSs to capture more image data. Therefore, Integrated scheduling problem for earth observation satellites is imperative, which optimizes data acquisition and data transmission simultaneously. In this paper, three different modelling frameworks, SSF, CSF and CISF, are investigated to formulate the ISPFEOS as a bi-objective optimization model along with an adaptive bi-objective memetic algorithm (ALNS + NSGA-II), which integrates the combined power of an adaptive large neighborhood search algorithm (ALNS) and a nondominated sorting genetic algorithm II (NSGA-II). In addition, two types of operators, “Destroy” operators and “Repair” operators, are designed to improve the ALNS + NSGA-II. Results of extensive computational experiments are presented which disclose that the CISF model produced superior outcomes.