摘要
当前,绿色物流网络的构建对企业物流系统的可持续发展起着至关重要的作用。文中研究了不确定情形下的绿色物流网络和库存问题,提出了一个考虑网络成本和CO2排放当量的双目标随机规划模型。其中,经济目标最小化网络总成本,包括订货成本、采购成本、运输成本、库存持有成本、延期交货成本和缺货损失成本;环境目标最小化运输过程的CO2排放,该过程基于《IPCC国家温室气体清单指南》中提出的测算方法和数据库进行。对于客户需求的可变性,采用情形树法进行描述,以客户需求不确定性的发生为界,将模型分为两个阶段进行分析。此外,文中对带精英策略的非支配排序遗传算法(NSGA II)进行改进求解上述模型,测试结果表明改进算法在收敛性能上明显优于原算法。文中模型和算法在一个两级供应链物流网络算例中的应用结果表明,环境目标的引入通过对订货、库存及运输方式决策产生影响来降低运作对环境的影响,决策者可以在小范围增加成本的前提下大幅度降低环境影响。此外,文中还对各决策过程关于延期配送的货物比例α的影响机理进行了分析。进一步说明了文中提出的模型和算法可以为各级决策者提供有效的订货、库存及车辆调度方案,以达到网络总成本和环境污染最小化的目的。
Nowadays, the establishment of green logistic network plays a vital role in the sustainable development of enterprise logistics system. The green logistics and inventory problem with uncertainty are studied. A bi-objective stochastic programming model considering network cost and CO2 emission equivalent is proposed. In the model, the cost objective minimizes the total cost including order cost, purchase cost, transport cost, inventory holding cost, delayed delivery cost and out-of-stock cost. The environmental objective minimizes CO2 emission during transport, which is calculated based on the proposed calculation method and database in IPCC National Green House Gas Inventories. The model is split into 2 stages for analyzing by the occurrence of uncertainty of customer demand, in which uncertainty is characterized by scenario tree. Furthermore, the modified NSGA II is adopted to solve the above model, the test result indicates that the adopted algorithm is superior to the original one in the aspect of convergence performance. Finally, the proposed model and algorithm are implemented into a 2-echelon supply chain case, the result shows that the introduction of environmental objective reduces the operational impact on the environment by influencing order, inventory, and transport decision-making. Decision makers can substantially reduce environmental impact at the expense of small increases in costs. In addition, the influence of the proportion α of delayed goods in each decision-making process is also analyzed. All conclusions reveal that the proposed model and algorithm can provide effective order, inventory and vehicle scheduling schemes to minimize total network cost and environment pollution.
作者
珠兰
胡大伟
ZHU Lan;HU Da-wei(School of Automobile, Chang＇an University, Xi＇an Shaanxi 710064, China)
出处
《公路交通科技》
CAS
CSCD
北大核心
2018年第6期121-130,共10页
Journal of Highway and Transportation Research and Development
关键词
交通工程
网络优化
随机规划
绿色物流
NSGA
Ⅱ
traffic engineering
network optimization
stochastic programming
green logistics
NSGA
