低碳政策下基于区间的模糊多式联运路径鲁棒优化研究

针对不同碳排放政策下模糊需求的路径优化问题,在综合考虑运输成本、转运成本、时间成本及碳排放成本的基础上,建立基于区间的鲁棒优化模型,并在强制碳排放、碳税、碳交易以及碳补偿政策下对模型进行低碳转换,采用基于蒙特卡洛采样的灾变自适应遗传算法求解。以具有15个节点的多式联运网络进行算例研究,比较不同低碳政策下多式联运总成本和碳排放量,并分析不确定参数的影响。结果表明:对于需求鲁棒性的最大保守值的合理设置有助于引导企业运输决策;碳补偿、碳税、碳交易和强制碳排放政策的减排力度逐步减弱;选择不同的碳排放政策并调节最大保守值可以达到控制碳排放且降低总成本的目的。     

低碳政策下基于区间的模糊多式联运路径鲁棒优化研究北大核心

针对不同碳排放政策下模糊需求的路径优化问题,在综合考虑运输成本、转运成本、时间成本及碳排放成本的基础上,建立基于区间的鲁棒优化模型,并在强制碳排放、碳税、碳交易以及碳补偿政策下对模型进行低碳转换,采用基于蒙特卡洛采样的灾变自适应遗传算法求解。以具有15个节点的多式联运网络进行算例研究,比较不同低碳政策下多式联运总成本和碳排放量,并分析不确定参数的影响。结果表明:对于需求鲁棒性的最大保守值的合理设置有助于引导企业运输决策;碳补偿、碳税、碳交易和强制碳排放政策的减排力度逐步减弱;选择不同的碳排放政策并调节最大保守值可以达到控制碳排放且降低总成本的目的。     

不同碳减排政策下考虑规模经济的多式联运路径选择研究

针对低碳多式联运路径选择问题,研究综合考虑运输成本、转运成本、时间成本以及强制碳排放、碳税、碳交易和碳补偿政策下的碳排放成本,构建多任务多式联运路径选择模型。设计精英-灾变混合自适应遗传算法求解,通过算例分析比较4种碳排放政策下的运输路径、方式、总成本和碳排放量及其变化情况,探索规模经济和碳减排政策的影响作用。研究结果显示：强制碳排放、碳税、碳交易以及碳补偿政策在制约机制方面存在差异,制约效果受到与其相关的环保要求、单位碳排放代价、总成本等多种因素的影响;订单合并产生的规模效应在多式联运减排和降本方面具有一定的积极作用。     

改进麻雀搜索算法求解多目标低碳冷链物流车辆路径问题

目的 在传统冷链物流的车辆路径问题模型基础上,考虑服务节点和车辆运输过程中产生的碳排放,并加入客户满意度,在有限资源情况下最小化路径成本和最大化客户满意度。方法 构建多目标低碳冷链物流车辆路径问题模型,将爬山算法局部搜索思想应用到麻雀搜索算法中,形成改进麻雀搜索算法,并用其对上海市某区域内的冷链物流配送路径优化问题算例进行求解。结果 通过与改进前及其他2种智能优化算法运行结果进行对比发现,改进后的麻雀搜索算法具有更快的寻优速度和更好的寻优能力,且改进后的算法对模型的碳排放效用性更高。结论 基于国家的低碳政策,设计出符合当下实情的低碳冷链物流运输模型,通过改进优化算法设计运输方案,验证了爬山算法局部搜索思想对麻雀搜索算法进行改进的有效性及所构建低碳冷链物流车辆路径模型的合理性。     

低碳环境下冷链物流企业库存-配送优化

目的 优化冷链物流企业库存-配送的路径,以降低企业冷链物流的成本.方法 考虑冷链物流企业库存和配送环节产生成本的因素,并结合我国关于碳减排的碳交易政策,将企业的碳排放代价同其他代价综合考虑,建立以总代价最低为目标的成本模型,设计并改进麻雀搜索算法进行计算.结果 通过使用MatlabR2018b进行仿真实验,将采用麻雀搜索算法计算的仓储-配送作业总代价与其他经典算法进行比较,在1个仓储配送任务内,代价可减少2％～4％,验证了麻雀搜索算法解决文中代价模型的有效性.结论 该研究为冷链物流企业库存-配送优化问题提供了一种新型的解决方法,具有较强的操作性和实际意义.     

改进麻雀算法求解低碳柔性作业车间调度问题

针对车间调度对制造业能源消耗和碳排放影响较大的问题,建立以最小化最大完工时间和碳排放量为目标的低碳柔性作业车间调度模型,采用改进的麻雀搜索算法求解。首先,通过三种不同的搜索方式对种群进行初始化,保证初始种群的质量。其次,引入正弦搜索策略,使个体根据自身位置的优劣采用不同的搜索策略,增强算法的搜索能力。再次,引入交叉和变异算子,避免算法迅速陷入局部最优。最后,通过Brandimarte数据集和实例仿真验证改进算法的性能。     

碳交易政策下零售商持股制造商减排投资决策

碳交易政策下,针对制造商低碳产品的高成本破解难题及零售商"搭便车"现象,引入零售商持股制造商减排投资战略,探讨股权合作下低碳供应链运作与协调策略。研究发现,对于清洁型制造商,碳交易价格的增加会使单位产品碳减排量增加,对于污染型制造商,碳交易价格的降低会使单位产品碳减排量增加。进一步发现,存在一定的零售商持股比例,能减少碳排放同时实现制造商和零售商收益的帕累托改进。随后,引入Shapley值法分配供应链利润,消除了持股前零售商"搭便车"现象及持股后制造商对供应链利润的分配优势,实现了增量利润在供应链成员间均等分配及供应链协调。最后,通过数值分析对结论进行验证并探讨了碳交易价格与持股比例对碳减排量和供应链成员利润的影响。     

低碳环境下废钢铁再加工生产调度优化

针对废钢铁再加工过程的工艺特点和约束条件设计了碳足迹计量方法,构建了最小化经济成本与碳交易成本总和的低碳调度模型。从理论分析和数值实验两方面探讨了碳限额、碳价及碳交易对总成本、碳排放和最优调度方案的影响。研究表明:废钢铁再加工低碳调度方案能有效减少碳排放,但可能会引起总成本的增加,若政府设置合理的碳限额,可大大提高废钢铁企业碳减排的积极性;碳限额的增大能有效降低总成本,对碳排放和最优调度方案无直接影响;高碳价促使废钢铁企业选择更具减排优势的加工设备、工艺路线和精料调度方案,从而降低碳排放,但过高的碳价对碳减排作用不大。     

随机需求下半开放式冷链物流车辆路径优化

目的 降低冷链物流配送成本的同时,保证客户体验及碳排放达到企业要求。方法 综合考虑运输距离、客户软时间窗约束、碳排放、生鲜变质等因素,以制冷成本及对配送时间惩罚成本在内的总成本最低、碳排放量最低、生鲜产品新鲜度最高为目标,建立多目标生鲜配送路径优化模型,并设计模拟退火算法,以北京某冷链物流企业为例进行求解验证。结果 得出生鲜配送方案,通过配送模式对比表明多中心半开放式在降本和缩短路径长度方面更具优势,其中运输总费用和车辆行驶总距离相比于单中心独立配送模式分别降低了8.41%和36.36%。结论 需求不确定下,合理决策路由可在达到企业对生鲜产品新鲜度及碳排放标准的同时,有效降低配送成本。     

基于阶梯碳交易的碳捕集电厂-电转气虚拟电厂低碳经济调度

在能源互补和低碳经济的背景下,虚拟电厂(virtual power plant,VPP)是实现区域资源优化配置和新能源消纳的有效载体。在技术层面,通过碳捕集电厂(carbon capture power plant,CCPP)和电转气(power-to-gas,P2G)装置来实现CO₂的循环利用,建立碳捕集电厂-电转气耦合模型,并在负荷侧引入考虑用户满意度的价格型需求响应模型;在低碳政策方面,将阶梯型碳交易机制引入VPP,对碳排放进行约束。然后以总成本最小为目标,建立VPP低碳经济调度模型。通过设置不同调度场景进行对比,验证所建模型在VPP低碳经济运行方面的有效性,并通过敏感性分析探究阶梯碳交易参数对VPP碳排放量与成本的影响,结果表明所建模型对VPP进行低碳经济调度具有指导意义。     

基于区块链的食品冷链质量安全信息平台构建

目的 研究区块链技术在食品安全领域,尤其是在生鲜食品冷链物流质量安全监测中的具体应用,以加强食品质量安全管理,提高食品冷链供应链效益.方法 分析生鲜食品冷链物流质量安全管理的薄弱环节,论证区块链技术的食品冷链质量安全监测适用性基础上,以区块链为底层技术构建食品冷链质量安全信息平台,研究区块链技术的创新应用对食品冷链质量安全管理的提升效果.结果 应用区块链技术构建了数据统一、运营高效的生鲜食品冷链质量安全信息平台,对食品质量安全信息进行了实时采集,实现了质量安全风险即时预警、质量安全问题有效溯源,有助于重塑食品质量安全生态系统.结论 区块链作为分布式账本、数字签名、溯源存证等一系列核心技术的组合,基于区块链技术创建食品冷链质量安全信息平台,能够强化微生物污染监测、缩短食品冷链在途时间,并使质量安全问题得到有效追踪溯源,对于加强食品质量安全管理、促进生鲜食品供应链优化有重要意义.     

Joint decisions on inventory replenishment and emission reduction investment under different emission regulations

Carbon emission regulation policies have emerged as mechanisms to control firms’ carbon emissions. To meet regulatory requirements, firms can make changes in their production planning decisions or invest in green technologies. In this study, we analyse a retailer’s joint decisions on inventory replenishment and carbon emission reduction investment under three carbon emission regulation policies. Particularly, we extend the economic order quantity model to consider carbon emissions reduction investment availability under carbon cap, tax and cap-and-trade policies. We analytically show that carbon emission reduction investment opportunities, additional to reducing emissions as per regulations, further reduce carbon emissions while reducing costs. We also provide an analytical comparison between various investment opportunities and compare different carbon emission regulation policies in terms of costs and emissions. We document the results of a numerical study to further illustrate the effects of investment availability and regulation parameters.     

Effects of carbon emission regulations on remanufacturing decisions with limited information of demand distribution

Policy-makers are developing regulation policies to drive down carbon emissions from industries. Independent remanufacturers (IRs), which remanufacture recycled products/components/parts, must manage and evaluate economic costs generated by the production under future carbon emission regulations. We present three optimisation models to determine the remanufacturing quantity that maximises the total profits under three common carbon emission regulation policies: (a) mandatory carbon emissions capacity, (b) carbon tax and (c) cap and trade. These models include sales revenue, remanufacturing cost, disposal cost, inventory holding cost, shortage cost and carbon emission cost. The max–min approach is used to solve the models, which assume limited information on demand distribution. We investigate how the three regulation policies affect remanufacturing decision-making for IRs and we also solve some numerical examples where we vary the magnitudes of incentives, penalties and stringency of constraints to provide implications to policy-makers. The results indicate that remanufacturers should aim to improve yield rate to maximise the profit irrespective of the implemented carbon emissions policy. Policy-makers should prefer the carbon tax policy, if any of the other two policies must be performed, a remanufacturing discount such as a higher carbon emission cap or lower penalty should be implemented to better promote the development of remanufacturers.     

An optimization study of a palm oil-based regional bio-energy supply chain under carbon pricing and trading policies

Biomass residues due to their low bulk density typically require frequent transportation from biomass plantations in rural areas to conversion bio-energy power plants. This issue contrasts with environmental protection strategies, especially when power plants are facing different carbon reduction policies that enforce them to emit less than a given specific carbon amount. Although several researchers have investigated bio-energy supply chains concerning environmental policies, the majority of studies have been devoted to strategic decisions over a single planning period. This paper presents a multi-period bio-energy supply chain under carbon pricing (carbon tax) and carbon trading (cap-and-trade) policies at the tactical planning level. A mixed-integer linear programming model was adopted to optimize the proposed regional oil-palm biomass-to-bio-energy supply chain planning model. The numerical results indicate that when carbon pricing is in place when carbon tax increases linearly, carbon emissions’ reductions have a nonlinear trend, whereas both cost increase and carbon emissions’ reductions have a relatively upward trend in the carbon trading scheme. This paper also presents the sensitivity analysis of the proposed model regarding cost, emissions’ generation and supply chain performance. Finally, the paper recommends several significant practical implications and policy-making insights for managers and policymakers.     

Financing Strategy of Low-Carbon Supply Chain with Capital Constraint under Cap-and-Trade Regulation

Cap-and-trade regulation provides incentives for manufacturers to reduce carbon emissions, but manufacturers’ insufficient capital can disrupt the implementation of low-carbon emission reduction technologies. To alleviate capital constraints, manufacturers can adopt external financing for low-carbon emission reduction investments. This paper studies the independent financing and financing cooperation behavior in a supply chain in which the manufacturer and retailer first implement low-carbon emission reduction technologies and then organize production and sales in accordance with wholesale price contracts. Through comparing the optimal profits and low-carbon emission reduction levels under the independent financing and financing cooperation mode, we come to the following conclusions: (1) Although financing interest increases the cost of the supply chain, manufacturers prefer to invest in reducing carbon emissions rather than buying carbon quotas. (2) When financing independently, a decentralized decision-making mode (MD) is the best choice for manufacturers. (3) In cooperative financing, when the supply chain adopts a decentralized decision-making mode (SD) in which the retailer determines the financing cost-sharing ratio according to their optimal profit, the profits of the supply chain and its members are significantly improved. (4) When manufacturers and retailers adopt a centralized decision-making model (SC) in cooperative financing, they jointly determine the financing cost-sharing ratio and the level of low-carbon emission reduction. If the financing cost-sharing ratio meets a certain threshold range, the profits of manufacturers and retailers achieve Pareto improvement, indicating that this cooperative financing model is effective.     

A green vendor-managed inventory analysis in supply chains under carbon emissions trading mechanism

One of the most important strategies for reducing carbon emissions is to optimize firms’ operation decisions in business practices. This paper proposes a green vendor-managed inventory (a green VMI) model with a supplier and a manufacturer under a carbon emissions trading mechanism. The proposed model integrates both environmental and economic goals under a carbon emissions constraint, and then the members’ optimal decisions are obtained. Comparing this model with the traditional VMI model, this paper finds that, in the green VMI model, whether the supplier should sell or buy carbon credit depends on the carbon cap. Further, the impacts of the carbon cap and the carbon emissions factors on the optimal decisions, the carbon emissions, and the total costs in the supply chain are examined analytically. Finally, numerical experiments are performed to verify the theoretical results. It is shown that, after introducing the carbon trading mechanism, the VMI model could increase the total cost of the supply chain under some specified set of parameters.     

Collaborative model for a two-echelon supply chain with uncertain demand under carbon tax policy

Consideration of carbon policies while optimizing supply chain operations has become imperative as governments and regulatory bodies throughout the world have implemented different carbon policies to reduce emissions of greenhouse gasses, especially CO₂. “Carbon tax” is one of the major carbon policies, initiated by several governments to curtail emissions. In this study, we have considered this policy to optimize the total expected cost (TEC) of a two-echelon integrated supply chain with stochastic demand, where both backorders and lost sales are permitted. An unconstrained mixed integer non-linear programming (MINLP) problem is formulated and further solved to find the optimal production rate, order quantity, number of shipments and reorder point while minimizing the TEC. Emissions from all the major sources such as production, inventory and transportation have been taken into consideration. It is assumed that the emission from production is a function of production rate, and emission from transportation depends on payload and vehicle type. This study will help organizations to reduce cost and emissions, and regulatory bodies to decide proper tax rate on carbon emission.     

碳交易下供应链中的技术创新激励合约设计

来自市场和政府的压力迫使企业进行低碳技术创新,完成减排目标。因此,在碳交易且信息不对称情况下,对制造商低碳技术创新投资决策和政府的激励合约展开研究。研究表明,信息不对称时,通过激励合约的设计,政府可以观察消费者低碳偏好程度实现最优激励;激励合约有效提高了制造商技术创新的动力,得出了制造商最优决策及影响因素;提出制造商和政府要通过广告、政策等方式努力提高消费者低碳偏好程度,达到降低碳排放的目的。