山东交通学院学报

针对冷链物流运输成本较高、货损率较大及碳排放突出等问题，基于时变路网，综合考虑冷藏车固定使用成本、运输成本、制冷成本、货损成本、时间惩罚成本以及碳排放成本等，构建以总成本最小化为目标的生鲜产品冷链配送路径优化模型。通过引入基于时间窗中心值与空间位置节约值的初始化策略、自适应参数控制机制、多层次局部搜索策略，并结合天鹰优化算法的全局搜索策略，提出改进非洲秃鹫优化算法，用于求解模型。仿真算例结果表明：在考虑碳排放成本的情况下，改进非洲秃鹫优化算法的总成本比原始非洲秃鹫优化算法降低约25.7%,所需车辆数从9辆减至7辆；目标函数中考虑碳排放成本时的配送总成本比忽略碳排放成本时降低约1.13%;改进非洲秃鹫优化算法的路径寻优能力显著优于传统算法，在兼顾碳排放成本的同时优化配送路径，达到物流成本降低与低碳配送的目标，为冷链物流配送路径优化提供有效解决方案。

To address the challenges of high transportation costs, elevated spoilage rates, and prominent carbon emissions in cold-chain logistics, this study develops a fresh-product cold-chain vehicle routing optimization modelover a time-dependent road network, aiming to minimize total cost. The model jointly considers fixed vehicle usage cost, transportation cost, refrigeration cost, spoilage cost, carbon-emission cost, and time-window penalty cost. An improved African vulture optimization algorithm(AVOA) is proposed to solve the model by introducing an initialization strategy based on time-window centers and spatial savings, an adaptive parameter-control mechanism, and a multi-level local search strategy, while incorporating the global search strategy of the aquila optimizer. Computational experiments show that, when carbon emissions are considered, the improved AVOA reduces total cost by about 25.7% compared with the original AVOA and decreases the required fleet size from 9 to 7 vehicles. Furthermore, the total cost when accounting for carbon emissions is about 1.13% lower than when carbon emissions are not considered. The improved AVOA demonstrates markedly superior route-search capability over traditional algorithms, simultaneously optimizing distribution routes while internalizing carbon-emission costs to achieve both cost reduction and low-carbon delivery. The proposed approach provides an effective solution for cold-chain logistics routing.