Cultivating Consensus: A Behaviourally-Grounded Positive Multi-Objective Programming Approach towards Sustainable Policy Outcomes in Flanders’ Agriculture

This research aims to develop a novel Positive Multi-Objective Programming (PMOP) methodology and apply it to model the agricultural sector in Flanders. The key innovation of this approach lies in extending Positive Mathematical Programming (PMP) — first proposed in 1995 and widely applied in agricultural economics — into a general multi-objective framework. This extension will enhance the economic interpretation of the model: evolving from PMP's ambiguous "invisible cost" calibration to calibration based on the Pareto frontier or decision-maker preferences. Furthermore, by incorporating advances such as noise studies in inverse optimisation, PMOP is expected to improve the numerical accuracy and robustness of calibration. Building upon this foundation and coupling it with biophysical models, the research will provide intellectual support for shock simulation and resource optimisation in Flanders' agricultural sector.