An adaptive large neighborhood search metaheuristic for agile satellite scheduling with time-dependent transition time

Liu, Xiaolu; Laporte, Gilbert; Chen, Yingwu; He, Renjie

doi:10.1016/j.cor.2017.04.006

Cited by 142 publications

(119 citation statements)

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“…The only paper on MSP with time-dependent transition times, thus also called the AEOS problem, is the work by Liu et al [9]. They develop an adaptive large neighborhood search algorithm for the AS-01 satellite, the first agile EOS from China.…”

Section: Literature Reviewmentioning

confidence: 99%

“…al [9] presented a fast insertion algorithm based on the forward time slack and backward time slack for each task, measuring the maximum amount of time by which the execution of a task can be shifted forward…”

Section: Insertion Operatormentioning

confidence: 99%

“…Compared with those insertion algorithms that determine the observation (visit) time of each task in the current solution [9][11], our insertion method can allow more candidate tasks to be inserted into the current solution, and greatly reduces the complexity of computing the actual observation time of each task.…”

Section: Fig 2 the Insertion Of A New Task Imentioning

confidence: 99%

“…As mentioned by Liu et al [9], different physical design and ability parameters lead to large differences between the AEOS in different countries in terms of capability, constraints and management. No common benchmark instances are available for the AEOS scheduling problem.…”

Section: A Test Instancesmentioning

confidence: 99%

“…It is difficult to compare our algorithm with previous algorithms specifically designed for other agile satellites such as PLEIADES satellite which is investigated in most of the previous works. Since we consider the same agile satellite AS-01 as in Liu et.al [9] and we want to compare the performance of our algorithm with theirs, we decide to use their test instances. The targets for observation are randomly generated with a uniform distribution in two regions: a Chinese area distribution and a worldwide distribution.…”

Section: A Test Instancesmentioning

confidence: 99%

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An Iterated Local Search Algorithm for Agile Earth Observation Satellite Scheduling Problem

Peng

Vansteenwegen

Liu

et al. 2018

2018 SpaceOps Conference

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The scheduling problem of an Agile Earth Observation Satellite is to schedule a subset of observation tasks among a set of candidates during their visible time windows in order to gain a maximum collected profit. Each pair of two consecutive tasks should satisfy the "time-dependent" transition time constraint, which contributes to the difficulty of solving the problem. To tackle this problem, a concept of "minimal transition time" which only depends on the observation start time of the previous task, is introduced. On this basis, we develop a fast and effective Iterated Local Search algorithm. A local search insert procedure is specifically designed to deal with time-dependent transition times and time windows. The experimental results on a variety of instances show that our algorithm performs very well in terms of solution quality and computation time and outperforms the state of the art.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Insertion Operatormentioning

confidence: 99%

Section: Fig 2 the Insertion Of A New Task Imentioning

confidence: 99%

Section: A Test Instancesmentioning

confidence: 99%

Section: A Test Instancesmentioning

confidence: 99%

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