Multi-satellite scheduling problem with marginal decreasing imaging duration: An improved adaptive ant colony algorithm. (February 2023)

• Record Type: Journal Article
• Authors: Zhou, Zhongbao; Chen, Enming; Wu, Fan; Chang, Zhongxiang; Xing, Lining
• Is Part Of: Computers & industrial engineering. Volume 176(2023)
• Publication Date: 2023-02
• Subjects: Multi-agile satellite -- Variable duration imaging -- Diminishing marginal return -- Task allocation operators -- IAACO; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108890
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We propose the multi-satellites and variable-duration imaging scheduling problem. We discuss the diminishing marginal effect between duration and profits. We design IAACO that performs well to solve the problem. The algorithm is tested with different task scales. Abstract: With the development of satellite technology, agile Earth Observation Satellites (AEOS) can achieve variable duration imaging. The correlation of decreasing marginal gain during observation between the observation profit and the observation duration has been found. For the first time, we apply the diminishing marginal return function between the observation time and the observation profit obtained by observation tasks, and we study the scheduling problem of multiple observations with variable duration. We propose an improved adaptive ant colony algorithm (IAACO) to solve the problem. Finally, we prove the problems can also obtain greater profits, and the algorithm is better than ACO and A-ALNS in terms of convergent profits by computational experiments regarding the parameters of the actual AEOS.