基于改进鲸鱼优化算法的冷链配送路径优化  

Cold Chain Distribution Path Optimization Based on Improved Whale Optimization Algorithm

作　　者：陆文星[1] 王璐 任少彤 李华[1] LU Wenxing;WANG Lu;REN Shaotong;LI Hua(School of Management,Hefei University of Technology,Hefei 230009,China)

机构地区：[1]合肥工业大学管理学院,安徽合肥230009

出　　处：《物流科技》2023年第24期145-150,共6页Logistics Sci-Tech

基　　金：国家自然科学基金重点资助项目(72131006);安徽省自然科学基金面上资助项目(2208085MG182)。

摘　　要：随着“互联网+”的不断发展,冷链物流也逐渐成为低碳物流发展的必然选择。以低碳为切入点进行研究,有助于实现企业与社会的利益均衡。在此基础上,文章建立了一个考虑碳排放的冷链配送模型,将Beta分布应用于鲸鱼优化算法(Whale Optimization Algorithm,WOA)进行种群初始化,再引入非线性收敛因子改善迭代后期陷入局部最优的情况,最后结合变邻域算法改进了鲸鱼优化算法来增加邻域结构的多样性,并将此算法应用于该模型求解。通过对文章提出的算法进行MATLAB实验验证,结果表明:与基本鲸鱼优化算法相比,文章提出的算法能够有效地降低物流配送成本,提高收敛速度和搜索能力,从而为冷链物流路径规划提供了新思路。With the continuous development of Internet Plus,cold chain logistics has gradually become an inevitable choice for low-carbon logistics development.Studying from a low-carbon perspective can help achieve a balance of interests between enterprises and society.On this basis,the paper establishes a cold chain distribution model considering carbon emissions,applies Beta Distribution to Whale Optimization Algorithm(WOA)for population initialization,and then introduces nonlinear convergence factor to improve the situation of falling into local optimum at the end of iteration.Finally,combined with variable neighborhood algorithm,the paper improves Whale Optimization Algorithm to increase the diversity of neighborhood structure,and applies this algorithm to solve the model.Through MATLAB experiment on the algorithm proposed in this paper,the results show that compared with the basic whale optimization algorithm,the algorithm proposed in this paper can effectively reduce the logistics distribution cost,improve the rate of convergence and search ability,thus providing a new idea for cold chain logistics path planning.

关 键 词：冷链物流 鲸鱼优化算法(WOA) 车辆路径优化 碳排放 BETA分布 

分 类 号：F252.1[经济管理—国民经济] TP183[自动化与计算机技术—控制理论与控制工程]