Designing a sustainable circular agriculture supply chain considering real-world business concerns

abstract

The transition from a linear to a circular economy in food and agriculture supply chains has attracted scholars and managers due to increasing demands and environmental concerns. Incorporating sustainability with circular supply chain and transportation systems, not only addresses global environmental issues but also prevents the excessive use of non-renewable resources while covering economic and social concerns. Contrary to earlier studies, this study proposes a new sustainable circular agriculture supply chain and logistics network, incorporating a multi-objective mixed-integer linear programming model that considers current important real-world business concerns, like water consumption, agrochemical use, and new Agrivoltaic technologies. These factors are integrated to enhance transportation efficiency, productivity, revenue, and employment. Key logistic components such as facility location, transportation, inventory, and warehousing are addressed within this optimization framework. The feasibility of the proposed network is evaluated through a case in Northern Iran, addressed by the General Revised Multi-Choice Goal Programming method. Besides, this study develops a new modified multi-objective meta-heuristic algorithm, alongside other famous ones, with a comprehensive tuning strategy to tackle the proposed test problems. The performance of the algorithms is evaluated by several indicators, and a new hybrid multi-objective decision-making approach is proposed to ease the comparison of the algorithms. Adjustments in influential logistics and transportation parameters and different aspects of the proposed problem are explored through several sensitivity analyses. The results highlight the importance of facility location, effective Agrivoltaic technology, strategic product transportation, and inventory planning, which enhance circular and sustainable advancements in agri-food transportation and logistic industries. © 2025 Elsevier Ltd