【摘要】 为实现农产品物流配送路径的合理规划和调度，降低物流配送成本和提高消费者满意度，对萤火虫算法进行改进，建立一种对农产品规划多目标物流配送路径的模型。针对传统萤火虫存在局部最优和收敛速度慢的缺点，提出一种云自适应萤火虫算法。选择物流配送成本最低和路径最短为目标函数，将萤火虫位置编码为车辆编号和车辆路径顺序，通过改进的萤火虫算法求解出多目标农产品物流配送的最佳路径。实验数据显示，对比经典的FA、GA等模型，CMAFA模型的搜索时间以及平均搜索耗能等方面，成本最小、效率最佳。此外，CMAFA的搜索成功率为67%，高于FA和GA的46%和25%，进一步证明了CMAFA模型对于农产品的物流配送路径选择及优化方面的强大优势。更多还原

【Abstract】 In order to achieve the reasonable planning and scheduling of agricultural products logistics distribution path,reduce the cost of logistics distribution and improve consumer satisfaction,a mathematical model for multi-objective planning of agricultural products logistics distribution path based on the improved firefly algorithm w as proposed. In view of the shortcomings of traditional firefly,such as local optimization and slow convergence speed,a cloud adaptive firefly algorithm w as proposed. The low est cost and the shortest path w as chosen as the objective function,the firefly position w as encoded as the vehicle number and the vehicle path order,and the optimal path of multi-objective agricultural product logistics distribution w as solved through the improved Firefly algorithm. The results show that,compared w ith FA and GA,CM AFA has the low est cost and the best efficiency in terms of search time and average driving cost. In addition,the search success rate of CM AFA is 67%,w hich is higher than 46% of FA and 25% of GA. It further verifies the effectiveness and reliability of CM AFA in agricultural logistics distribution path optimization.更多还原