Multi-objective planning of a multiple geostationary spacecraft refuelling mission

Zhou, Yang; Yan, Ye; Huang, Xu; Yang, Yueneng

doi:10.1080/0305215x.2016.1190352

Cited by 10 publications

(2 citation statements)

References 18 publications

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“…Scholars at home and abroad have invested a lot of research on the problem of OOS mission planning. Zhou et al [2] studied the problem of refueling satellites in GEO and employed double-layer optimization, incorporating genetic algorithms and precise numerical algorithms. The upper layer and the lower layer were optimized separately to achieve the optimal energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Mission Planning for Spacecraft On-orbit Service Based on Hybrid Variant Particle Swarm Optimization

Wang,

Lyu,

Zhao

et al. 2024

J. Phys.: Conf. Ser.

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For the complex on-orbit service (OOS) mission planning problem, an improved hybrid variant particle swarm optimization (PSO) method was proposed to improve the fuel utilization efficiency of spacecraft. Firstly, considering the time and fuel constraints, a model for OOS mission planning under the scenario of multiple target spacecrafts is established. The Lambert orbit maneuver method is used and the problem is transformed into a large-scale hybrid nonlinear integer programming problem. Next, an improved hybrid variant PSO algorithm is designed to optimize the fuel performance cost, and its simple structure and lightweight operation facilitate autonomous planning, considering the limited computing power of the onboard computer. The hybrid algorithm is composed of discrete particle swarm optimization (DPSO) and PSO, so it has a strong ability to search for the optimal service sequence and orbit maneuver time simultaneously. Moreover, the adaptive and variant operators are used to improve the searching ability and avoid falling into local optimal solutions. Finally, simulation experiments show that the proposed method can quickly give optimal results, reducing fuel consumption effectively in the OOS mission and improving the OOS capability of the spacecraft.

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Section: Introductionmentioning

confidence: 99%

Autonomous Mission Planning for Spacecraft On-orbit Service Based on Hybrid Variant Particle Swarm Optimization

Wang,

Lyu,

Zhao

et al. 2024

J. Phys.: Conf. Ser.

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“…The best economy will be achieved if multiple spacecraft can be serviced in a single mission [10,11]. Mission planning problem arising from servicing multiple spacecraft began to attract attention recently.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Mission Planning for Multiple Geosynchronous Spacecraft Refueling

Kong,

Zhou

2023

International Journal of Aerospace Engineering

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This paper studies the multiple geosynchronous spacecraft refueling problem (MGSRP) with multiple servicing spacecraft (Ssc) and fuel depots (FDs). In the mission scenario, multiple Ssc and FDs are parked in the geosynchronous Earth orbit (GEO) initially. Ssc start from FDs and maneuver to visit and refuel multiple GEO targets with known demands. These capacitated Ssc are expected to rendezvous with fuel-deficient GEO targets and FDs for the purpose of delivering the fuel stored in FDs to GEO targets. The objective is to find a set of Pareto-optimal solutions with minimum fuel cost and mission duration. The MGSRP is a much more complex variant of multidepot vehicle routing problems mixing discrete and continuous variables. A two-nested optimization model is built. We propose a new multiobjective hybrid particle swarm optimization to solve the outer-loop problem, and the design variables are the refueling sequence, task assignment, time distribution, and locations of FDs. In the inner-loop problem, branch and bound method is used to find the optimal decision variable for a given outer-loop solution. Finally, numerical simulations are presented to illustrate the effectiveness and validity of the proposed approach.

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Optimal Rescheduling for OOS Mission Based on Squeaky-Wheel Optimization

Dong

Chen³

2022

Proceedings of the 7th China High Resolution Earth Observation Conference (CHREOC 2020)

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Multi-objective planning of a multiple geostationary spacecraft refuelling mission

Cited by 10 publications

References 18 publications

Autonomous Mission Planning for Spacecraft On-orbit Service Based on Hybrid Variant Particle Swarm Optimization

Autonomous Mission Planning for Spacecraft On-orbit Service Based on Hybrid Variant Particle Swarm Optimization

Multiobjective Mission Planning for Multiple Geosynchronous Spacecraft Refueling

Optimal Rescheduling for OOS Mission Based on Squeaky-Wheel Optimization

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