Abstract
In the era of artificial intelligence (AI), many industry sectors, including space exploration, have experienced a shift in the way business is conducted due to the widespread use of AI technologies. In the past few years, AI has become a key tool used to explore the universe in space missions. In this paper, a multi-objective optimal design for payload orbital transfer involving space tethers is proposed based on a computational intelligence-assisted design framework with the artificial wolf pack algorithm (AWPA). Enlightened by the social behaviors of a wolf pack and its swarm intelligence, the AWPA is utilized for optimization problems in which a logsig function randomly obtains assignments for parents and offspring. Swarmwolf , a simulation toolbox with given initial conditions. The proposed method effectively performs optimization tasks based on index of evolutionary pathway trends, has been defined to demonstrate the optimizing process. The results show that the proposed approach works expeditiously for the optimization of space tether model and its application.
| Original language | English |
|---|---|
| Article number | 8890637 |
| Pages (from-to) | 161449-161458 |
| Number of pages | 10 |
| Journal | IEEE Access |
| Volume | 7 |
| DOIs | |
| State | Published - 2019 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2013 IEEE.
Keywords
- Artificial intelligence
- artificial Wolf-pack algorithm
- computational intelligence assisted design
- evolutionary pathway
- multi-objective optimization
- payload orbital transfer
- space tether
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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