Multi-criteria optimization and estimation in the presence of uncertainty. Application to the selection of multi-performance plant varieties in the presence of environmental variability

• Title: "Multi-criteria optimization and estimation in the presence of uncertainty. Application to the selection of multi-performance plant varieties in the presence of environmental variability"; INRAE.
• Postdoctoral researcher: Minh-Lien Nguyen.
• Affiliated unit: INRAE, UMR 1404 - MaIAGE – Dynenvie.
• Project duration: 2023–2024.

Project summary:

The objective of this post-doctorate is to develop a mathematical methodology and implement it for multi-criteria optimization, integrating random components describing the plant's environment (climate, soil...). It will also involve establishing its theoretical properties and quantifying its practical performance. The targeted criteria will include traditional ones, such as yield and economic value. Additional criteria might include carbon footprint and aspects related to plant morphology in the context of mixed or associated cropping. This simultaneous optimization of multiple objectives will enable the selection of plant varieties that are profitable, eco-friendly, and robust in the context of climate change. The wheat yield data used comes from an experiment involving 220 wheat varieties observed in 42 environments with contrasting cultivation and climate conditions.