Many objective robust decision-making model for agriculture decisions (MORDMAgro)

Abstract

Each year, farmers must decide crops and their agronomical management for the plots of their farms. This decision—subject to climatic interaction and crop prices context—will determine farm earnings. We introduce a framework, called MORDMAgro, based on Many Objective Robust Decision-Making methodology to support farmers' decisions. Through the use of a scenario approach, the framework aims to assist in situations where there is no agreement on how to represent the uncertain critical parameters that affect the outcome, that is, crop prices or weather conditions. It considers seven decision objectives that focus on costs, margins, utilities, returns, losses, gains, and regrets to integrate a comprehensive range of farmers’ goals. The framework outputs robust strategies to farmers, that is, land allocation to crops that return acceptable outcomes for as many scenarios as possible, rather than finding an “optimal” strategy that optimizes one or several objectives. It also identifies critical scenario factors that decrease a decision's payback by a classification tree algorithm. We applied the framework to a case study of a farm in the Argentine Pampas to identify robust strategies from typical cropping alternatives based on wheat, maize, and soybean. We share all scripting and data to ensure reproducibility and foster the framework's usage.