Optimizing Crop Selection Using Genetic Algorithms

Date

7/12/2021

Journal Title

Journal ISSN

Volume Title

Publisher

50th International Conference on Environmental Systems

Abstract

Interstellar Lab develops bioregenerative habitats and agriculture systems, which are naturally centered around crop cultivation. These systems are very sensitive to which plants are grown, since it determines land area, water consumption, and lighting power requirements. Hence, we developed an innovative crop selection algorithm (CSA) to address these challenges. This CSA is designed for the following purposes: (1) to fully cover the nutritional requirements of the crew, (2) to ensure the dietary diversity of the daily intake, (3) to minimize the water and land usage, and (4) to schedule crop cultivation and ensure optimal use of available growing area. To tackle this, we developed a Genetic Algorithm (GA), known to perform well on this type of tasks. A population of crop selections and schedules is generated and evaluated through an objective function to select the ones that perform well. The top performers reproduce in the next generation, and mutations are applied until an optimal solution is found. Interstellar Lab believes our approach is the first step towards a bioregenerative system that puts crop selection and scheduling in the center of the BioPods that comprise our Experimental BIOregenerative Station (EBIOS).

Description

Yixuan Yang, Interstellar Lab
Maarten Smits, Interstellar Lab
David Kas, Interstellar Lab
Jeremy Jauzion, Interstellar Lab
Graham Gordon, Interstellar Lab
ICES204: Bioregenerative Life Support
The 50th International Conference on Environmental Systems was held virtually on 12 July 2021 through 14 July 2021.

Keywords

Crop Selection, Algorithm, Bioregenerative, Optimization, Agriculture

Citation