“双碳”背景下废钢企业逆向物流网络优化

钢铁行业的碳排放量占全国碳排放量的15%-20%,逆向物流废钢再利用的降碳空间巨大。聚焦废钢企业逆向物流体系,以网络建设与运营过程中碳排放成本以及其他经济成本最低化为目标,对废钢设施选址、货流分配等内容进行优化决策,考虑流量平衡、基地容量约束、运载工具容量约束等限制条件,构建了废钢企业逆向物流网络优化模型。基于遗传算法和蚁群算法设计了一种双层嵌套启发式算法进行求解;外层遗传算法确定选址方案,代入内层蚁群算法求解货流分配方案,再返回外层遗传算法求解最终目标值,经过多次迭代寻优得到最终方案。最后以江苏地区废钢企业逆向物流网络为研究对象进行算例分析,验证了模型与算法的可行性。该研究成果可为废钢企业逆向物流网络建设和运营决策提供有效支撑。     

碳交易背景下生鲜电商前置仓选址问题研究

为了解决生鲜电商在选址过程中忽视碳排放量的不足之处,以生鲜电商前置仓为例,在充分考虑前置仓选址的约束问题前提下,根据货损成本、改造成本、运营成本、制冷成本以及处理低碳排放成本,构建一个以最小总成本为目标的选址模型,并针对模型的特征选取对应的编码方式、交叉和变异算子,设计遗传算法对模型进行求解。算例结果进一步证明了该模型与算法的有效性,并为碳交易环境下生鲜电商物流设施节点选址提供了有益借鉴。     

带有多级制造环节的供应链能力分配方法及应用

提出了一种带有多级制造环节的供应链模型,并建立了多目标、多变量、多约束的混合整数非线性数学模型,建立了一种基于邻域搜索的约束满足算法,设计了算法的编码方式、邻域构造方法、变量选择和值选择规则等一系列算法实现细节,并构造了基于理想点思想的适应度函数以实现对多目标的处理。通过使用C#语言实现了基于邻域搜索的约束满足算法,钢铁企业实际数据实验验证了算法的可行性和实用性。     

基于多目标模糊线性规划方法的低碳承运商选择研究

随着环保意识增强和政府环保政策陆续出台,物流承运商的选择决策时需要考虑碳排放等环境因素的影响.文章在传统运输成本和服务质量目标的基础上,增加了承运商满意度和碳排放量目标准则,构建了一个基于模糊多目标线性规划方法的承运商选择模型.算法和算例结果表明,该模型能够有效地解决现实经济活动中考虑多个准则因素的承运商选择决策问题.     

考虑新鲜度的多目标绿色冷链路径优化问题与算法

针对冷链物流配送中碳排放成本较高以及客户对生鲜品新鲜度要求较高的问题,为了满足企业降低综合配送成本,提高配送效率,实现低碳绿色出行的目标,构建了以碳排放量、平均新鲜度、综合配送成本为目标的多目标车辆路径模型。然后设计将变邻域算子融入自适应遗传算法中,对模型进行求解,解决了遗传算法过早成熟的问题,提高了算法的求解效率。最后进行算例计算和对比分析,不断调整算例范围,验证了模型和算法的有效性,为提高送达时生鲜品的新鲜度水平,降低碳排放量,辅助企业进行实际配送抉择提供了新思路。     

高铁运输参与的多目标绿色多式联运路径优化

针对低碳要求下高铁参与的多式联运路径优化问题,考虑节点处各运输方式班期限制和运力差异以及收货时间窗约束等因素,构建了以运输成本、碳排放量和物流服务满意度为目标的多目标绿色多式联运路径优化模型。为提高模型求解效率,提出了改进基于参考点的非支配排序遗传算法。基于案例数据,对模型进行了求解,验证了模型和算法的有效性。针对运量和顾客收货时间窗变化等因素进行实验分析,结果揭示了各目标随运量和时间变动而变化以及高铁利用率变化的特征,可为多式联运经营人提供多差异性需求的有效运输方案。     

动态需求下的多目标配送中心选址研究

为弥补现有选址模型未考虑需求变化的不足,研究了非确定性需求环境下的配送中心选址问题;运用随机机会约束规划为基本建模工具,建立了配送中心动态选址模型;模型不仅考虑最小化物流成本,而且考虑了最大满意度;运用主要目标法将多目标选址模型转化为单目标选址模型,并构造了相应的贪婪启发式求解算法,算例结果表明了模型和算法的有效性。     

碳排放限额约束下的供应链优化模型研究

文中从供应链整体设计框架出发,针对碳排放限额约束建立了以经济和环境为多目标的数学模型,对供应链网络进行了优化并用一个算例验证了模型。该供应链网络优化模型有一定的创新性,能够给企业带来管理启示与参考价值。     

基于公平的拥堵收费和可交易电子路票的多模式物流网络优化模型

基于拥堵收费和可交易的电子路票建立了多模式物流网络优化模型。模型考虑了商品所有者的收入对多模式物流网络下配送需求的产生、配送模式的选择以及配送路径选择的影响,得到了物流网络流畅策略对不同配送商品价值和地域分组的物流需求分配的影响。模型被描述为带有均衡约束的数学规划问题,并可通过无导数算法求解。     

动态需求下的多目标配送中心选址研究

为弥补现有选址模型未考虑需求变化的不足,研究了非确定性需求环境下的配送中心选址问题;运用随机机会约束规划为基本建模工具,建立了配送中心动态选址模型;模型不仅考虑最小化物流成本,而且考虑了最大满意度:运用主要目标法将多目标选址模型转化为单目标选址模型,并构造了相应的贪婪启发式求解算法,算例结果表明了模型和算法的有效性.     

政企双层规划下考虑碳配额的供应链网络优化

构建了政企互动决策下考虑碳配额的双层规划模型,随后采用多目标粒子群优化算法求解模型,最后解析碳配额和需求不确定置信水平变化对供应链网络Pareto最优解集的影响。研究表明政企互动决策过程中存在最优碳配额,且随着政府部门根据双寡头制造商的反馈合理调整碳配额,上层规划模型中政府部门考虑双寡头制造商反馈的调整系数增大,双寡头制造商能够引导其它供应链企业减少间接碳排放,导致供应链网络总成本和碳排放持续减少。随着市场需求不确定置信水平升高,需求预测的精度降低,各设施间流量增加,需要增设备选设施,供应链网络总成本和碳排放也随之增加。     

The Environmental Outcome of Emissions-intensive Economic Growth: A Critical Look at Official Growth Projections for Sweden up to the Year 2000

Implications for carbon dioxide, sulphur dioxide and nitrogen oxides emissions from the Swedish government's medium-term economic projections are assessed, considering Sweden's environmental goals. Data from the first environmental accounting matrix of Sweden are exploited within the framework of the interindustry model to give emission multipliers for various components of aggregate demand. In view of these emission multipliers, it is evident that the outlined macro-economic development does not conform with Sweden's environmental goals. The oil price and the structural changes assumed in the economic projections stress still further the need for strong environmental policy measures to attain the emission goals. The allocation of total expenditure is shown here to be a critical factor for bringing down the emissions to accepted levels.     

长三角地区城市平稳增长下能源碳排放需求估计

探讨了城市能源碳排放需求预测的研究方法,采用最优增长率模型,研究了经济平稳增长条件下,长三角地区各个城市未来的能源碳排放需求。结果显示,长三角地区大部分城市碳排放需求的高峰值都出现在2025年以前,只有上海出现在2040年,这将使上海面临较大的减排压力。南京、苏州、宁波和无锡的能源消费需求、能源碳排放需求都较高,人均碳排放也超出全国平均水平,因此,未来这些城市也将面临较大的减排压力。     

Industrial clusters with substantial carbon-reduction potential

To successfully reduce environmental emissions, companies need to expand the scope of their emissions accounting to include entire supply chains. A clustering approach has been used to find emission-intensive industry clusters. However, this approach did not include entire direct and indirect supply chains when forming high emission industry clusters. We propose a new method based on a modified normalized cut function with Leontief’s input–output model and basic clustering algorithms to find industry clusters with high levels of embodied within-cluster emissions that are well separated in the supply chain network. We use this method to identify 58 carbon-intensive clusters of Japanese industries and visualize the within-cluster supply chains in terms of embodied carbon flows. We recommend that companies collaborate within clusters to reduce environmental emissions. Our results provide new insights on where to target emissions reduction actions and technology development within industrial supply chains.     

A CARBON FOOTPRINT TIME SERIES OF THE UK – RESULTS FROM A MULTI-REGION INPUT–OUTPUT MODEL

The framework and results of an international multi-region input–output (MRIO) model for the UK are presented. A time series of balanced input–output tables for the UK was constructed for the period 1992 to 2004 by using a matrix balancing procedure that is able to handle conflicting external data and inconsistent constraints. Detailed sectoral and country-specific trade data for the UK were compiled and reconciled with the UK input–output data, and economic and environmental accounts for three world regions were integrated in a UK-specific MRIO model. This was subsequently used to calculate a time series of national carbon footprints for the UK from 1992 to 2004. Greenhouse gas emissions embedded in UK trade are distinguished by destination of imports to intermediate and final demand. Most greenhouse gases show a significant increase over time in consumer emissions and a widening gap between producer and consumer emissions. Net CO₂ emissions embedded in UK imports increased from 4.3% of producer emissions in 1992 to a maximum of 20% in 2002. The total estimated UK carbon footprint in 2004 was 730 Mt for CO₂ and 934 Mt CO₂ equivalents for all greenhouse gases.     

考虑碳排放因素的车辆路径问题研究

将碳排放因素考虑到车辆路径问题中,建立了运输成本与碳排放相结合的多目标车辆路径问题模型,讨论了基于改进遗传算法的车辆路径问题的设计和实现,最后通过实例分析对模型作了进一步验证。     

城市交通碳排放分析及实证研究

城市经济发展使得城市交通迅速发展,同时也造成了能源消耗过多、排放污染加剧。文章构建数学模型对城市交通子系统碳排放进行分析,并以西安市为例进行实证分析。结果表明,城市私人载客汽车和道路运输营运部门是主要交通碳排放源,占总排放的67%以上,并且有序发展私人交通、改变交通需求结构、提高能源利用率能有效降低城市交通碳排放。     

Developing an emission risk control model in coal-fired power plants for investigating CO2 reduction strategies for sustainable business development

The climatic risk consists of financial and environmental risks, predominantly evolutes from carbon dioxide emissions from coal-fired power plants. We develop a climatic risk control model to investigate the coexistence of renewable energy and the post-combustion carbon capture technology as CO₂ reduction strategies. Additionally, our proposed framework explicitly considers the acceptance of such strategies based on a balance of electricity supply according to demand. This paper adopts an additive fuzzy mixed-integer optimization approach to model uncertain parameters and determines the optimal solution focusing on business and the environment. Furthermore, we investigate the feasibility of such emission control strategies with scenario analysis that help to execute the country's emission reduction policies. The usefulness of our methodology is demonstrated using data from the coal-based power sector in the Eastern part of India. Overall, with the proposed model, we can achieve 30% reduction in emission release, which provides strategies to the decision-maker for investment towards sustainable development.     

Impact of Carbon Dioxide Emissions Reduction on the Austrian Economy

A linked econometric input–output (IO) model of the Austrian economy with an energy block is used in this study to assess the sectoral effects of carbon dioxide emissions reduction. The energy block and the other commodities are linked by a partitioned IO model. Energy demand is described using aggregate energy demand equations, by activities and subdemand systems of the translog type for different fuel types. The conversion of energy is modelled using an IO model of the energy sector. Measures for carbon dioxide reduction from detailed expert studies are introduced in the energy model and in the econometric model. The primary impacts are on energy demand, fuel shares and investment in new energy technologies. The simulation results of the partitioned IO model show different impacts on gross output, GDP and employment.     

碳约束下需求离散随机的库存控制问题研究

文章站在零售商的角度,通过分析需求离散随机库存控制过程中的碳排放因素,设计出基于碳排放成本的随机库存控制模型,对低碳供应链中库存控制的要素进行了分析,并通过算例来说明该模型。模型有利于进一步提升供应链的核心竞争力,推动低碳供应链管理的深入研究。