Sustainability in organic and non-organic agricultural supply chain: an integrated planning-pricing model with demand dynamics and hybrid metaheuristic optimization

The growing importance of Environmental, Social, and Governance (ESG) concerns in sustainable food systems has increased attention on organic agriculture. As demand for organic products rises, supply chain decisions such as pricing, inventory management, and advertising have become more complex and interdependent. This study presents a multi-objective mathematical model designed to support integrated decision-making within a sustainable supply chain that includes both organic and non-organic agricultural products. The model considers a centralized, forward-moving supply chain structured across three tiers: production centers, distribution centers, and retailers. It incorporates demand dynamics linked to both sales price and advertising, capturing how consumer preferences shift over time and how local advertising influences product substitution during shortages. The model is formulated as a mixed-integer linear programming problem with three main objectives: maximizing total profit, minimizing environmental impact, and enhancing social benefits through healthier consumption. For small problem sizes, an exact epsilon-constraint method is used. For larger cases, we introduce a hybrid metaheuristic called MOPSBBO, which combines Particle Swarm Optimization (PSO) with Biogeography-Based Optimization (BBO). Numerical results validate the model’s performance and highlight key insights. Strategic pricing increases both sales and profitability, while a combination of media and environmental advertising raises demand for organic products. Local advertising also encourages consumers to substitute non-organic products with organic ones during shortages, promoting sustainable choices and improving supply chain outcomes.