Space station overall mission planning using decomposition approach

Lin, Kun-Peng; Luo, Yuling; Zhang, Jin; Tang, Guojian

doi:10.1016/j.ast.2013.12.012

Cited by 11 publications

(4 citation statements)

References 16 publications

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“…A hierarchical model was proposed, with different layers such as mission planning, trajectory generation and vehicle navigation. Similarly, Lin et al (2014) proposed a hierarchical, three-level, decomposed framework to model the overall mission planning problem. In this framework, the first-level problem deals with the top-level mission scenario parameters, the second-level problem deals with the vehicle visiting strategy and the third-level problem deals with flying orbital missions.…”

Section: Mission Planningmentioning

confidence: 99%

Integrated maintenance and mission planning using remaining useful life information

Camci

Medjaher

Atamuradov

et al. 2018

Engineering Optimization

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The modern world requires high reliability and availability with minimum ownership cost for complex industrial systems (high-value assets). Maintenance and mission planning are two major interrelated tasks affecting availability and ownership cost. Both tasks play critical roles in cost savings and effective utilization of the assets, and cannot be performed without taking each other into consideration. Maintenance schedule may make an asset unavailable or too risky to use for a mission. Mission type and duration affect the health of the system, which affects the maintenance schedule. This article presents a mathematical formulation for integrated maintenance and mission planning for a fleet of high-value assets, using their current and forecast health information. An illustrative example for a fleet of unmanned aerial vehicles is demonstrated and evolutionary-based solutions are presented.

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Section: Mission Planningmentioning

confidence: 99%

Integrated maintenance and mission planning using remaining useful life information

Camci

Medjaher

Atamuradov

et al. 2018

Engineering Optimization

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“…However, the maintenance spares uploaded were not considered to quantify the utilization benefit, which instead greatly affect the benefit through the distribution of crew work time, and the total number of both cargo and manned vehicles was too simplified to identify the operational cost [7]. Ho et al [8] studied a two-objective optimization model for the concurrent design of space station crewed habitats and logistics systems to gain a higher scientific return with lower cost.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Space Station’s Operational Scenario Parameters Using Physical Programming

Lin

Luo

Tang

2015

Journal of Spacecraft and Rockets

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“…Barreiro et al [10] developed a Peer-to-Peer prototype application which supports crew planning and power planning for the ISS separately. In the overall mission planning domain, Lin et al [11] studied the overall planning of space station long-term mission using a decomposition approach. Lin et al [12] studied the space station long-duration orbital mission planning problem under multi-constraints.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of space station short-term mission planning

Zhang

Luo

et al. 2015

Sci. China Technol. Sci.

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This paper studies the multi-objective optimization of space station short-term mission planning (STMP), which aims to obtain a mission-execution plan satisfying multiple planning demands. The planning needs to allocate the execution time effectively, schedule the on-board astronauts properly, and arrange the devices reasonably. The STMP concept models for problem definitions and descriptions are presented, and then an STMP multi-objective planning model is developed. To optimize the STMP problem, a Non-dominated Sorting Genetic Algorithm II (NSGA-II) is adopted and then improved by incorporating an iterative conflict-repair strategy based on domain knowledge. The proposed approach is demonstrated by using a test case with thirty-five missions, eighteen devices and three astronauts. The results show that the established STMP model is effective, and the improved NSGA-II can successfully obtain the multi-objective optimal plans satisfying all constraints considered. Moreover, through contrast tests on solving the STMP problem, the NSGA-II shows a very competitive performance with respect to the Strength Pareto Evolutionary Algorithm II (SPEA-II) and the Multi-objective Particle Swarm Optimization (MOPSO). space station, short-term mission planning, multi-objective optimization, NSGA-II Citation:Bu H J, Zhang J, Luo Y Z, et al. Multi-objective optimization of space station short-term mission planning.

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Space station overall mission planning using decomposition approach

Cited by 11 publications

References 16 publications

Integrated maintenance and mission planning using remaining useful life information

Integrated maintenance and mission planning using remaining useful life information

Optimization of Space Station’s Operational Scenario Parameters Using Physical Programming

Multi-objective optimization of space station short-term mission planning

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