Using an effective tabu search in interactive resources scheduling problem for LEO satellites missions

Sarkheyli, Arezoo; Bagheri, Alireza; Ghorbani-Vaghei, B.; Moghadam, Reza Askari

doi:10.1016/j.ast.2013.04.001

Cited by 45 publications

(24 citation statements)

References 14 publications

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“…Zhu et al [31] simulated the scheduling scenario for Chinese Yao Gan, Feng Yun and Zi Yuan satellites using a genetic annealing method and built the PEM environment as well. To cope with the integrated satellite scheduling problem in the HEM environment, Sarkheyli established a constraint satisfaction model including energy capability, cloud coverage and data memory, where the memory-erasing event was categorized as a type of special task [32], but the optimization on the memory-erasing events was not addressed in this study.…”

Section: Related Workmentioning

confidence: 99%

Integrated agile observation satellite scheduling problem considering different memory environments: a case study

Xing

Chen

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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This paper presents an experimental study on an integrated agile earth observation satellite (AEOS) scheduling problem involving the satellite memory environments of the partially erasable memory (PEM) and the holistically erasable memory (HEM). The integrated AEOS scheduling problem simultaneously considers the satellite observation and transmission events, in which the onboard memory functions as a very important connective resource. To address the memory constraints in the AEOS scheduling problem, an integrated AEOS scheduling model that is suitable for both the PEM and HEM environments is proposed in this paper. Based on commonly used construction heuristic and meta-heuristics, two hybrid approaches, Tabusimulated annealing (TSA) and Tabu late acceptance (TLA) algorithms, are adopted to solve this problem. The highlights in this paper are the formulation of novel adaptive memory constraints for the AEOS scheduling and the quantitatively scheduling comparison of separated and integrated modeling methods. Experimental results indicate that (1) the memory environment has a direct influence on the AEOS integrated scheduling results, where the PEM environment sufficiently utilizes memory resources and advances the efficiency of the AEOS a lot. (2) The integrated scheduling method enables the reduction in resource consumption and obtains a better result than the separated scheduling method, especially in the HEM environment, (3) and the hybrid meta-heuristics TLA and TSA that show better overall performance are suggested for addressing the studied AEOS integrated scheduling problem.

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Section: Related Workmentioning

confidence: 99%

Integrated agile observation satellite scheduling problem considering different memory environments: a case study

Xing

Chen

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…Xhafa et al [15] also designed an adaptive mutation probability genetic algorithm, when studying the task planning problem of Earth observation satellites. Sarkheyli et al [16], in a study of low-orbit satellite task planning, took task priority, resource constraints and user satisfaction into consideration and designed a new tabu search algorithm to solve them. Ruan et al [17] adopted the greedy algorithm for task planning and solving.…”

Section: Overview Of Satellite Task Planning Algorithmsmentioning

confidence: 99%

A Satellite Task Planning Algorithm Based on a Symmetric Recurrent Neural Network

Liu

Yang

2019

Symmetry

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The intelligent satellite, iSAT, is a concept based on software-defined satellites. Earth observation is one of the important applications of intelligent satellites. With the increasing demand for rapid satellite response and observation tasks, intelligent satellite in-orbit task planning has become an inevitable trend. In this paper, a mixed integer programming model for observation tasks is established, and a heuristic search algorithm based on a symmetric recurrent neural network is proposed. The configurable probability of the observation task is obtained by constructing a structural symmetric recurrent neural network, and finally, the optimal task planning scheme is obtained. The experimental results are compared with several typical heuristic search algorithms, which have certain advantages, and the validity of the paper is verified. Finally, future application prospects of the method are discussed.

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“…Marinelli et al [16] developed a Lagrangian version of the Fix-and-Relax MIP heuristic to solve the large scale input variables for satellite scheduling problem. Sarkheyli et al [17] modeled the scheduling problem as the graph coloring and proposed a new tabu search algorithm to solve resources scheduling in low earth orbit by a new move function. Wu et al [18] presented a novel two-phase based scheduling method in task clustering phase and task scheduling phase, constructed an acyclic directed graph model, and utilized a hybrid ant colony optimization algorithm for satellite observation scheduling.…”

Section: Introductionmentioning

confidence: 99%

Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

Wang

Dai

Vasile

2014

Mathematical Problems in Engineering

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Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

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Using an effective tabu search in interactive resources scheduling problem for LEO satellites missions

Cited by 45 publications

References 14 publications

Integrated agile observation satellite scheduling problem considering different memory environments: a case study

Integrated agile observation satellite scheduling problem considering different memory environments: a case study

A Satellite Task Planning Algorithm Based on a Symmetric Recurrent Neural Network

Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

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