Scheduling multiple agile Earth observation satellites

Chao Han, Xinwei Wang, Guopeng Song and Roel Leus

No 627938, Working Papers of Department of Decision Sciences and Information Management, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven

Abstract: Earth observation satellites (EOSs) are specially designed to collect images according to user requirements. Agile EOSs (AEOSs), with stronger attitude maneuverability, greatly improve the observation capability, while increasing the complexity of scheduling the observations. We are the first to address multiple AEOSs scheduling with multiple observations where the objective function aims to maximize the entire observation profit over a fixed horizon. The profit attained by multiple observations for each target is nonlinear in the number of observations. Our model is a specific interval scheduling problem, with each satellite orbit represented as a machine. A column-generation-based framework is developed for this problem, in which the pricing problems are solved using a label-setting algorithm. Extensive computational experimtents are conducted on the basis of one of China’s AEOS constellations. The results indicate that our optimality gap is less than 3% on average, which validates our framework. We also evaluate the performance of the framework for conventional EOS scheduling.

Keywords: Agile Earth observation satellites; Integer programming; Column generation heuristic; Interval scheduling (search for similar items in EconPapers)
Pages: 30
Date: 2018-10
New Economics Papers: this item is included in nep-cmp
Note: paper number KBI_1813
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Published in FEB Research Report KBI_1813

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Persistent link: https://EconPapers.repec.org/RePEc:ete:kbiper:627938

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