面向多车场冷链物流配送的改进正余弦算法  

Enhanced Sine-Cosine Algorithm for Multiple-Depot Cold Chain Logistics Distribution Optimization

作　　者：路世昌[1] 刘丹阳 LU Shichang;LIU Danyang(School of Business and Management,Liaoning Technical University,Huludao,Liaoning 125105,China)

机构地区：[1]辽宁工程技术大学工商管理学院,辽宁葫芦岛125105

出　　处：《计算机工程与应用》2024年第9期326-337,共12页Computer Engineering and Applications

基　　金：辽宁省教育厅人文社会科学研究项目(21-A817)。

摘　　要：以冷链物流为对象,研究了一类考虑多中心联合配送和硬时间窗约束的调度问题。基于问题描述建立了以最小化总成本为目标的数学模型。提出了改进正余弦算法(enhanced sine-cosine algorithm,ESCA)以获取当前问题的满意解。结合问题特征创建了融合构造式规则的编解码方法,并辅以个体评估方法实现模型与正余弦算法(sine-cosine algorithm,SCA)的适配。同时,将反向学习机制嵌入ESCA的初始化流程,旨在提升初始解的性能。在种群进化方面,构建了融合双种群机制、非线性参数调节和随机扰动的混合进化机制以平衡寻优过程的全局探索和局部挖掘行为,并通过离散邻域搜索方法避免搜索停滞。开展了案例研究和算法对比实验,结果验证了ESCA算法的良好性能。This work deals with a multiple-depot cold chain logistics distribution optimization problem with consider�ations of hard time windows.Firstly,the problem domain is presented and the programming model is formulated to mini�mize the total cost.Then,an algorithm named ESCA is developed for solution methodology.By virtue of the problem nature,a novel constructive encoding and decoding method,as well as an evaluation function,are designed to adjust SCA to the considered problem.Meanwhile,the opposition-based learning method is embedded into SCA to improve perfor�mance of initial solutions.To balance exploration and exploitation abilities,a hybrid individual update method is designed by combing the multi-population mechanism,the non-linear transition and the random perturbation.In addition,a discrete neighbor search method is used to avoid search stagnation.Finally,experiments on the case study and the algorithm com�parison analysis are concocted to validate the efficiency of ESCA.

关 键 词：优化 调度 正余弦算法 混合 邻域搜索 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]