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作 者:曹庆奎 崔金超 任向阳 CAO Qingkui;CUI Jinchao;REN Xiangyang(School of Management Engineering and Business,Hebei University of Engineering,Handan 056038,Hebei,China;Faculty of Economics and Management,Langfang Normal University,Langfang 065000,Hebei,China)
机构地区:[1]河北工程大学管理工程与商学院,河北邯郸056038 [2]廊坊师范学院经济与管理学院,河北廊坊065000
出 处:《上海海事大学学报》2024年第4期32-38,共7页Journal of Shanghai Maritime University
基 金:国家自然科学基金(61375003);河北省教育厅人文社会科学研究重大课题攻关项目(ZD202105)。
摘 要:为有效应对冷链物流配送中电动汽车电量限制的挑战,考虑交通流的连续变化特性以及冷链物流配送的多中心趋势,引入车辆电量约束,将电动汽车的能耗成本加入目标函数,构建时变网络下多中心电动冷藏车配送路径优化模型。设计一种改进蚁群算法,通过优化初始信息素和调整转移概率以扩大邻域搜索范围,并引入模拟退火算法的回火机制和限制信息素浓度以避免算法陷入局部最优解。仿真结果表明:所提出的模型能够有效解决电动车辆在冷链物流配送中的电量限制问题;改进的蚁群算法能降低配送成本,缩短配送距离,具有收敛速度快、效率高的特点,从而验证了算法的有效性。In order to effectively address the challenge of electric vehicle power limitation in the cold chain logistics distribution,considering the continuous change characteristics of traffic flow and the multi-center trend of the cold chain logistics distribution,the vehicle power constraint is introduced,the energy consumption cost of electric vehicles is added to the objective function,and a multi-center electric refrigerated vehicle distribution path optimization model under time-varying network is constructed.An improved ant colony algorithm is designed,the neighborhood search range is expanded by optimizing the initial pheromone and adjusting the transfer probability,and the tempering mechanism of simulated annealing algorithm and limiting the pheromone concentration are introduced to avoid the algorithm falling into the local optimum solution.The simulation results show that,the proposed model can solve the problem of power limitation of electric vehicles in cold chain logistics distribution effectively;the improved ant colony algorithm can reduce the distribution cost and shorten the distribution distance,and has the characteristics of the fast convergence and high efficiency,thus verifying the effectiveness of the algorithm.
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