Sustainable Agriculture Through Multi-Objective Decision Making: A Goal Programming Approach

Abstract

Sustainable agriculture has become a priority in the whole world due to the growing demand of food and the need to maintain the available natural resources. Contemporary agriculture has to recon opposite goals of a farm business, namely, to achieve the highest possible crop productivity; to ensure the lowest possible cost of inputs; and to limit the environmental effects of resources consumption, specifically, water and fertilizers. The proposed study aims at developing a goal programming (GP) model to optimize these conflicting objectives under a sustainable agricultural system. In the model proposed, four main objectives are included, which are to minimize water consumption, fertilizer amount, maximize the crop yield, and finally minimize the overall cost of production. The model determines the most appropriate input combinations that give balance between productivity and sustainability by assigning priorities and weights to each goal. The model can be tested with real or simulated farm-level data, which shows that it can help to make data-driven decisions when planning agricultural activities. The findings indicate that goal programming is a viable instrument that can be applied to manage trade-offs in sustainable agriculture to provide farmers, agronomists, and policymakers with realistic information that can be applied to improve food security without compromising environmental resources.