考虑低碳政策和不确定需求的物流网络鲁棒优化OA北大核心CHSSCDCSSCICSTPCD
Robust Optimization of Logistics Network Considering Low-carbon Policy and Uncertain Demand
为应对全球气候变暖,将政府调控政策融入供应链网络设计是物流业低碳转型面临的一项挑战.为此,本文研究考虑低碳政策和不确定需求的物流网络设计问题.首先,运用分布式模糊集刻画产品需求的不确定性,并构建供应链物流网络的两阶段鲁棒优化模型.该模型在经典的三级网络规划基础上,综合考虑分销中心建设成本、运输成本、产品短缺成本以及碳排放交易的负效用以实现总成本最小化.其次,针对提出模型的两阶段特点,对其进行拆分为主问题和子问题并定制迭代分解算法.最后,结合案例验证所提出的模型及分解算法的有效性.数值结果表明:提出的分布式鲁棒优化方法在提高决策方案鲁棒性的同时可有效减少其所需投资;低碳政策虽然会促进物流企业调整运输结构、降低碳排放总量,但仍然会增加企业的总成本,建议政府部门可适当考虑补贴.
In response to global warming,the Chinese government will adopt more effective policies and measures,which aim to peak carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060.Such an ambitious goal has brought great challenges to various industries by changing the mode of operation management and implementing the transformation of the low-carbon economy.In terms of the total carbon emissions in China,the transportation sector currently accounts for about 10.4%,of which the road is the main carbon emission con-tributor,accounting for 87%.It is an important and necessary way to achieve the emission reduction target through the optimization and reconstruction of the cargo transportation system.In terms of government regulation policies,the mostly discussed are carbon emission cap-and-trade and carbon tax.They are set to internalize the cost of carbon emissions,encourage enterprises to actively optimize their logistics network structure,and promote the transport mode from road to cleaner rail and water transport.China began implementing a carbon cap-and-trade policy in eight pilot cities in 2011,and established a carbon emission trading market in 2021.Therefore,the integration of carbon cap-and-trade policy in the design of supply chain logistics networks and the construc-tion of multi-mode transport systems are effective ways for enterprises to transform low-carbon. The classic facility location problem focuses on the goals of cost,efficiency,and social welfare improvement while ignoring the environmental impacts of transportation activities.The design of the supply chain logistics network has a significant two-stage property:during the effective period of facility planning decisions,the future product demand is changed by economic and social development and affects the decision of the enterprise.In recent years,probabilistic distributed fuzzy sets have been widely used to reduce their conservatism and improve their robustness by constructing fuzzy sets according to confidence levels from probability distribution information in historical data.In addition,the robust optimization method is an effective method to solve the optimization problem considering uncertainty.Relevant research provides a comprehensive optimization framework for supply chain logistics network design,but this method does not involve how to reconstruct the distributed robust model into a standard programming model that can be directly used by commercial solvers,which can design an efficient solution. Therefore,this paper studies the design of a supply chain logistics network under product demand uncertain-ty and carbon cap-and-trade policy.Considering the uncertainty of future product demand,a norm-based fuzzy set is proposed to describe the probability distribution of uncertain demand.Given the carbon emission reduction and trading policies,a two-stage robust optimization model for supply logistics network design is constructed to optimize the number and scale of distribution centers and the multi-mode transportation scheme of products.Based on the classic three-level network planning,the model comprehensively considers the distribution center construction cost,transportation cost,product shortage cost,and the negative utility of carbon emission trading to minimize the total cost.Considering the separability of the model,this paper reconstructs the main model and submodels and proposes a solution method based on column and constraint decomposition.Finally,the validity of the proposed robust optimization model and decomposition algorithm is verified by a practical case. The numerical results show that the proposed distributed robust optimization method can improve the robust-ness of the decision scheme and reduce its investment effectively.The greater the demand uncertainty,the grea-ter the number and scale of distribution centers expected to be built,which in turn increases the corresponding expected construction costs,transportation costs,carbon acquisition,and total costs.In order to realize the carbon emission reduction target,government departments can encourage enterprises to implement low-carbon production planning and operation in combination with policies such as subsidies for low-carbon transport modes.It is also important to strengthen the supervision of carbon emissions and assess the emission reduction perform-ances under different incentive measures.When the carbon quota is abundant,enterprises should pay more attention to reducing the transportation cost.And when the quota is scarce,the focus will be on how to reduce transport carbon emissions.
蒋杰辉;盛典
湖南财政经济学院 工商管理学院,湖南 长沙 410205华中科技大学 管理学院,湖北 武汉 430074
交通运输
供应链物流网络需求不确定低碳政策鲁棒优化
supply chain logistics networkuncertain demandlow-carbon policyrobust optimization
《运筹与管理》 2024 (008)
79-85 / 7
国家自然科学基金资助项目(72204078,72271103)
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