Background
Food cold chain logistics (FCCL) maintains low-temperature conditions during circulation and thus reduces food loss. However, FCCL requires significant consumption of energy, refrigerants, and other resources, resulting in substantial greenhouse gas emissions. Consequently, FCCL faces complex and ubiquitous conflicts among multiple sustainable goals (e.g., food quality, economic efficiency, and environmental impact) across various perspectives and scales. Coordinating mixed objectives and reconciling conflicting decisions are essential to ensure sustainable FCCL.
Scope and approach
This study establishes performance evaluation criteria for FCCL sustainability, identifying the main conflicts from various perspectives: foundational refrigeration mechanisms, micro-level low-temperature circulation, meso-level supply operation, and macro-level industrial policy. Recent progress in intelligent optimization is reviewed across different perspectives; further the current challenges and future trends are analyzed and summarized.
Key findings and conclusions
FCCL is undergoing a digital and sustainable transformation as it transitions into the Industry 4.0 era, with intelligent decision-making tools playing a pivotal role in sustainability-driven optimization. Intelligent optimization methods increasingly address the complexity of real-world cold chain dynamics, focusing on multi-stage, multi-agent, and multi-region interactions while improving accuracy, timeliness, and generalizability. The profiles of optimization vary under different application scenarios: refrigeration system design emphasizes flexibility, stability and low-carbon emissions; environmental control prioritizes precision, efficiency, and continuity; operations management stresses product safety and stakeholder benefits; and industry development highlights regional adaptation and environmental protection. Future breakthroughs in multimodal information fusion, demand-driven supply coordination, and spatiotemporal resource matching are expected to advance the sustainable self-optimization of FCCL, particularly through the multi-agent collaborative framework integrating digital twins and vertical large models. This review not only advances the theoretical understanding of sustainability conflicts and intelligent optimization mechanisms in FCCL, but also offers actionable guidance for industry stakeholders and policymakers to support data-driven, low-carbon, and scalable cold chain transformation.


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