考虑碳配额差值的选址-路径-库存集成问题优化模型与算法

考虑碳配额差值对产供销一体化系统中的选址-路径-库存集成问题的影响,构建了嵌入碳配额差值和选址-路径-库存运作成本的非线性整数规划模型,并对模型中的碳配额差值和选址-路径-库存运作成本两个目标同时进行优化;通过对目标函数进行等价处理,设计了基于BFA-PSO的组合优化求解算法;数值仿真结果显示企业可以通过运作层的决策优化,以较小的经济成本获得较大的碳减排绩效。     

Optimal production,replenishment, delivery,routing and inventory management policies for products with perishable inventory

This paper presents a generalized production-inventory-routing model with perishable inventory. We analyze the optimal integrated decisions of when and how much to deliver and sell products with varying manufacturing periods. We discuss main inventory management policies to demonstrate the applicability of the model in real-world applications for production routing problems (PRPs) with perishable inventory. Furthermore, an exact branch-and-cut algorithm is developed and discussed. We introduce new families of logical, strengthened lot-sizing and lifted Miller–Tucker–Zemlin subtour elimination constraints for the PRP with perishable inventory. Finally, we test the performance of the algorithm. We also implement and compare 8 suboptimal delivery and selling priority policies with an optimized policy to develop managerial implications.     

低碳环境下的车辆路径问题及禁忌搜索算法研究

基于节能减排的新视角,本文研究了低碳环境下由第三方提供运输服务的车辆路径问题,在安排车辆路径时,同时考虑了能耗、碳排放和租车费用,而这些费用不仅与距离有关,也与客户点的需求量和车辆速度有关。提出了考虑车辆运量和速度的能耗计算方法,建立了非满载运输方式下的低碳路径模型——LCRP。设计了基于路径划分的禁忌搜索算法RS-TS对问题进行求解,该算法引入了一种新颖的路径编码与解码算法WSS,采用了三种邻域搜索方法。通过基准测试实例验证了算法能有效地找到满意解,并揭示了距离、能耗、行驶时间等参数之间的关系,实验分析表明采用低碳路径安排更加经济环保且选择中低的交通速度更有利于节约能耗和降低碳排放。     

碳配额交易政策下基于收益共享契约的两阶段供应链协调

历史强度下降法分配碳配额随时间和产量变化而变化,产品生产成本、销售价格等参数随之发生变化,碳配额交易政策下实现两阶段供应链协调成为制造企业亟需解决的问题。根据产品更新换代速度加快、生命周期越来越短的市场特性及碳配额阶梯状降低的特点,将产品销售周期分为两个阶段,通过构建两阶段的集中式决策系统模型和收益共享契约下分散式决策系统模型,分析碳配额交易政策下供应链最优订购量决策和最优碳减排决策,证明收益共享契约可以通过调整零售商的订购量达到集中决策下的最优订购量实现两阶段供应链协调,设置较低的收益共享契约参数将会更有利于制造商降低批发价格,主动进行碳减排投入。算例分析验证结论有效性,并发现供应链企业间设置较低的收益共享比例更有利于企业减排;企业碳减排决策应考虑未来减排投入成本,在保证供应链效益的基础上尽可能多地在前期进行减排投入;历史强度下降法有利于促使企业主动减排,政府制定碳配额下降幅度越大越有利于企业减排。     

顾客有限“碳行为”偏好对选址-路径-库存联合优化的影响

针对考虑顾客有限“碳行为”偏好的选址-路径-库存联合优化问题,引入环保度系数作为碳排放量的特征向量,在低碳产品加价率存在的情况下,刻画了顾客有限“碳行为”偏好和市场逆需求系数对低碳产品需求量的影响,构建了选址-路径-库存系统中考虑有“碳行为”偏好的联合优化模型,并分析了顾客行为偏好对企业收益的影响。使用基于NNC的多目标求解方法,对考虑成本和碳排放的双目标问题进行处理并得到一组Pareto解集,数值实验证明了产品环保度、顾客有限“碳行为”偏好对企业运作方案和收益水平的影响。     

制造系统生产单元碳排放核算模型

制造业是我国国民经济的支柱产业，但也是环境污染物排放的主要来源、能源消耗主体和温室气体排放大户。制造系统高能耗、高物耗、高碳排放的加工过程是造成制造业碳排放量大的重要原因。生产单元作为制造系统的加工的主体，其碳排放量的核算是确定整个制造系统乃至制造业碳排放总量的关键。本文首先对生产单元的原材料、电能、辅助物料及废屑处理所引起的碳排放进行分析，确定生产单元的碳排放源；其次，产品合格率的不同会造成生产单元输入及输出的成品/半成品数量的差异，进而影响生产单元单位产品的碳排放量，在此基础上，综合考虑了原材料、电能、辅助物料及废屑处理的碳排放情况，构建了给定工艺流程下生产单元碳排放核算模型。最后，结合一汽车排气装置加工实例，分别核算加工过程中九个生产单元的碳排放量，验证了模型的可行性。     

考虑不同碳排放处理模式的动态供应商选择及采购批量问题研究

不同的碳排放处理模式及不确定的市场需求等因素影响下,如何选择供应商并确定采购批量直接影响企业的运营和效益。本文在多时间周期、多产品种类、多供应商及随机需求情形下,同时考虑不同碳排放处理模式,分析动态供应商选择及采购批量等最优决策问题,构建混合整数非线性规划模型。通过设计变异算子和扰动因子来改进粒子群算法,力求在短时间内求解大规模决策问题。针对不同规模供应商选择及采购批量决策问题,采用精确方法、近似方法和改进粒子群算法求解。数值实验验证了模型及改进粒子群算法的有效性和可行性,分析了碳税、碳交易价格及碳限额对供应链管理的影响,并给出了供应商选择及碳排放处理的决策参考建议。     

A continuous-time supply-driven inventory-constrained routing problem

We address an inventory routing problem (IRP) in which routing and inventory decisions are dictated by supply rather than demand. Moreover, inventory is held in containers that act as both a storage container and a movable transport unit. This problem emanates from logistics related to biogas transportation in which biogas is transported in containers from many suppliers to a single facility. We present a novel and compact formulation for the supply-driven IRP which addresses the routing decisions in continuous-time in which inventory levels within the containers are continuous. Valid inequalities are included and realistic instances are solved to optimality. For all experiments, we found that the total transportation time is minimized when the storage capacity at each supplier is larger than or equal to the vehicle capacity. These routes are characterized by tours in which mostly single suppliers are visited. In 95% of the instances, the average content level of the exchanged containers exceeded 99.6%.     

配额——交易机制下动态批量生产和减排投资策略研究

随着我国碳排放交易市场的建立和发展,在碳排放约束下逐步降低单位产出的碳排放水平成为企业生产经营管理中的中长期约束性目标。本文在一个多周期决策模型中研究了配额-交易机制下企业的最优动态批量生产、碳排放权交易和减排投资联合决策问题。生产商在整个决策周期期初决定是否进行减排投资以及投资规模,根据每个周期的生产计划决定减排设备的运行计划。根据节能减排技术的特点,本文假设生产商运行减排设备时不仅降低了产品的单位生产碳排放量,而且降低了产品的单位生产成本。本文基于广义Benders分解法对模型进行了最优性分析,得到了最优生产决策和最优减排投资决策的一些基本性质,并通过数值实验分析了碳排放配额和碳排放权价格对生产商总成本、总排放以及减排投资决策的影响。本文的数值实验分析结果发现:(1)当碳交易市场上的碳排放权充足时,减少碳排放配额或改变碳排放配额的分配方式并不能影响生产商的碳排放水平;(2)碳排放权价格是影响生产商的碳排放水平和减排投资规模的关键因素;(3)随着碳排放权价格的上升,即使拥有足够的碳排放配额,生产商仍会不断提高减排投资规模以获得减排收益。研究结果对碳排放交易体系下生产企业进行减排技术投资具有较强的管理启示。     

Inventory routing problems in a context of vendor-managed inventory system with consignment stock and transshipment

The inventory routing problem involves the integration and the coordination of two components of the logistics value chain: the inventory management and the vehicle routing decisions. In fact, the aim is to jointly decide on the distribution tour, from a distribution centre to a set of locations, and on the inventory policy for each location. Although many research investigations show great interest in policies such as transshipment or dynamic routings on the distribution system performances, these approaches are often criticised in practice as being too restrictive. In this article, we consider the inventory routing framework in a supplier integration context, i.e. a vendor-managed inventory with a consignment stock policy. Under such framework, we show that the transshipment brings more benefits than the classical context. In particular, we consider the case of static routings and we numerically show that transshipment permits to better optimise the distribution tours and to improve the global performance of the supply network.     

Analysis of Travel Times and CO2 Emissions in Time‐Dependent Vehicle Routing

Due to the growing concern over environmental issues, regardless of whether companies are going to voluntarily incorporate green policies in practice, or will be forced to do so in the context of new legislation, change is foreseen in the future of transportation management. Assigning and scheduling vehicles to service a pre‐determined set of clients is a common distribution problem. Accounting for time‐dependent travel times between customers, we present a model that considers travel time, fuel, and CO₂ emissions costs. Specifically, we propose a framework for modeling CO₂ emissions in a time‐dependent vehicle routing context. The model is solved via a tabu search procedure. As the amount of CO₂ emissions is correlated with vehicle speed, our model considers limiting vehicle speed as part of the optimization. The emissions per kilometer as a function of speed are minimized at a unique speed. However, we show that in a time‐dependent environment this speed is sub‐optimal in terms of total emissions. This occurs if vehicles are able to avoid running into congestion periods where they incur high emissions. Clearly, considering this trade‐off in the vehicle routing problem has great practical potential. In the same line, we construct bounds on the total amount of emissions to be saved by making use of the standard VRP solutions. As fuel consumption is correlated with CO₂ emissions, we show that reducing emissions leads to reducing costs. For a number of experimental settings, we show that limiting vehicle speeds is desired from a total cost perspective. This namely stems from the trade‐off between fuel and travel time costs.     

灰色量子粒子群优化通用向量机的中国行业间碳排放转移网络预测研究

针对行业间碳排放转移量预测问题，以中国1997-2017年间9年度28个行业间碳排转移量数据为样本，本文提出了基于小样本随机振荡序列的灰色量子粒子群优化通用向量机混合预测模型ROGM-QPSO-GVM。该模型首先使用ROGM（1，1）模型得到各行业对其他行业碳排放转移量的预测序列和残差序列，然后提出了一种新的量子粒子群优化（QPSO）算法优化GVM模型网络参数，构建了QPSO-GVM模型对残差序列进行修正，再将两部分的预测值相加得到行业间碳排放转移量预测值，最后根据所有预测值构建出行业间碳排放转移网络。结果表明ROGM-QPSO-GVM模型与其他模型相比具有更好的预测效果，并利用该模型对2020年、2025年、2030年中国行业间碳排放转移网络进行了预测及变化趋势分析。     

碳税政策下随机双渠道库存与协调研究

构建碳税政策下由单个制造商和单个零售商组成的双渠道供应链模型,在考虑渠道之间缺货转换的基础上,研究批发价格合约和双向收入共享契约下渠道间双渠道库存竞争问题,并设计了由双向收入共享合约和转移支付机制组成的组合合约机制使制造商和零售商实现共赢,以此保证合约的有效执行。研究表明：批发价合约和双向收入共享合约下,制造商分别通过调控批发价格和收入分享比例来调控双渠道的库存水平,其中网络渠道最优库存水平随着零售渠道单位碳排放量增加而增加,零售商的库存水平随着其单位碳排放量增加而减少。进一步分析了渠道间单位产品碳排放差异对批发价格,以及传统零售渠道和网络渠道库存水平的影响如何受到缺货转换率和碳税税率的调节。     

能源补贴改革对资源效率和环境污染治理影响研究——基于动态CGE模型的分析

本文构建动态CGE模型,以化石和可再生能源补贴政策为对象,模拟不同类型能源补贴政策改革对经济发展、资源效率、碳排放及雾霾治理的差异性影响。研究表明：总体而言,能源补贴政策对宏观经济具有积极的促进作用,但在一定程度上会提高能源消费强度;不同类型的能源补贴政策方案影响的差异性较大,化石能源在促进经济增长的同时,对环境改善和碳排放目标实现产生不利影响,特别是煤炭补贴能有效降低能源使用成本,极大促进产业总产出和经济增长,但会不利于环境改善,对可再生能源补贴有利于能源利用效率提高和人均资源盈余改善,降低污染物和雾霾排放增速;因此,必须注重不同类型能源补贴政策协调性和差异性,短期内以化石能源补贴为主,长期而言,应逐步加大可再生能源补贴,更加有利于低碳转型和环境改善。     

火力发电企业离散决策及其对碳排放权价格影响

随着碳交易市场的建立,对于参与减排企业,如何制定合理的减排决策从而降低减排成本成为了一个重要问题。在有效市场下,参与减排企业的边际成本将直接影响碳排放权价格的走势。以往研究大多基于连续时间模型,运用动态优化原理解决此类问题。而事实上,企业的决策过程是离散的,这是由于碳排放权不能跨期交易,如果简单连续化会使得企业有过度减排的可能,与现实不符。基于此,本文以电力企业为例,运用动态优化方法,建立电力企业的离散减排决策模型,从而得出企业的最优边际减排成本,为政府调控碳排放权市场提供理论指导。为了验证模型,本文采用深圳碳排放权的相关实际数据进行数值模拟。研究表明,当企业做出离散减排决策时,企业的减排成本及边际减排成本与初始排放量、配额、单位惩罚成本、减排决策次数等因素相关。企业的离散决策会使得企业的边际减排成本波动加大,进而可能引起碳排放权市场的动荡,但企业的离散决策更有利于企业完成减排任务。     

不同权力结构下碳税对供应链减排水平的影响

随着我国生态文明建设的不断推进,促进供应链协同减排成为生产和消费领域落实绿色发展理念的重要举措。在绿色供应链的管理实践中,不同类型的供应链核心企业在进行减排决策时会有不同的侧重点,因此供应链权力的结构成为影响供应链减排水平的关键因素。本文在一个由两个制造商和一个零售商组成的两级供应链中研究了不同权力结构下的供应链最优减排和定价决策问题,分别给出了零售商主导和制造商主导的Stackelberg-Nash博弈均衡解,并分析了产品的单位生产成本、单位批发价格、碳税税率等参数对供应链最优决策的影响。本文的研究结果表明：（1）在两种供应链权力结构下,当产品的单位批发价格固定时,降低产品的生产成本都可以促使制造商提高减排水平;但是当产品的单位生产成本固定时,提高产品的批发价格却不一定总是能够激励制造商提高减排水平;（2）在两种供应链权力结构下,对于低排放行业的制造商来说,提高碳税税率可以增加产品的减排水平,但是对于高排放行业的制造商来说,提高碳税税率反而会降低产品的减排水平;（3）一般来说,零售商占主导地位的供应链中产品减排水平和供应链总利润相对较高,供应链碳排放总量相对较低。最后,与供应链集中决策模式相比,随着产品批发价格的增加,两种分散决策模式下的供应链双重边际效应逐渐增强。数值实验结果显示：在碳税税率的一定取值范围内,这种双重边际效应会使得两种分散决策模式下的产品最优减排水平和供应链碳排放总量均优于集中决策模式。本文的研究可为碳税政策下供应链的协同减排提供有益的管理启示。     

Life cycle emission distributions within the economy: implications for life cycle impact assessment.

Refinements of methods for life cycle impact assessment (LCIA) are directed at removing unjustified simplifications and quantifying and reducing uncertainties in results. The amount of uncertainty reduction that is actually achieved through LCIA method refinement depends on the structure of the life cycle inventory model. We investigate the general structure of inventory models using an economic input/output (I/O) life cycle assessment model of the U.S. economy. In particular, we study the results of applying a streamlining algorithm to the I/O LCA model. The streamlining algorithm retains only those "branches" of the process tree that are jointly required to account for a specified fraction of the total impacts upstream of each point in the tree. We examine the implications of these "tree pruning" results for site-informed LCIA. Percentiles are presented for U.S. commodities and several important pollutants, for the share of total upstream emissions contributed by the set of processes in each supply tier, that is, each set of processes that directly supply inputs to another set of processes Capturing at least 90% of the total direct plus upstream emissions for criteria air pollutants and toxic releases for at least 75% of the commodities in the U.S. economy requires full modeling of direct emissions plus the first five supply tiers. The requirements for capturing a high percentage (e.g., >80%) of total emissions vary widely across products or commodities. To capture more than 60% of total emissions for more than half of all commodities requires models with more than 4,000 process instances. To well characterize the total impacts of products, life cycle impact assessment methods must characterize foreground process impacts in a site-informed way and mean impacts of far-removed processes in an unbiased way.     

Vendor managed inventory in tramp shipping

This paper introduces a new problem to the OR community that combines traditional tramp shipping with a vendor managed inventory (VMI) service. Such a service may replace the more traditional contract of affreightment (COA) which for decades has been the standard agreement between a tramp shipping company and a charterer. We present a mathematical formulation describing the routing and scheduling problem faced by a tramp shipping company that offers a VMI service to its customers. The problem is formulated as an arc-flow model, and is then reformulated as a path-flow model which is solved using a hybrid approach that combines branch-and-price with a priori path-generation. To solve larger, and more realistic, instances we present a heuristic path-generation algorithm. Computational experiments show that the heuristic approach is much faster than the exact method, with insignificant reductions in solution quality. Further, we investigate the economic impact of introducing a VMI service, by comparing the results obtained with the new model with results obtained by solving the traditional routing and scheduling problem faced by tramp shipping companies using COA. The computational results show that it is possible to substantially increase supply chain profit and efficiency by replacing the traditional COAs with VMI services.     

Modeling and solution of practical management problems through netforms

This paper shows some useful schemes to graphically depict netform models of practical inventory problems. We begin with a simple inventory problem and then progress to more comprehensive representations of an inventory system by network and netform model techniques. Some text books mention that very basic inventory problems may be modeled as networks. But they usually offer very little instruction in the actual development of a network inventory model, and invariably conclude that network models can't accommodate the complications of the vast majority of realworld inventory problems. Further, they completely fail to convey the modeling power available to more general netform (network-related formulation) techniques. As text books catch up to the recent innovations now being applied in practical settings, this deficiency will change. Our purpose is to introduce the fundamental ideas and to provide an understanding of the possibilities inherent in these model innovations. We begin from first principles, so that no prior familiarity with network model representations is necessary to follow the exposition. Because of a heavy reliance on pictorial illustrations (another of the unique advantages of networks and netforms), we have also avoided the use of complex mathematical notation, and develop the key concepts by informal discussion.     

An oracle-based algorithm for robust planning of production routing problems in closed-loop supply chains of beverage glass bottles

The demand for glass bottles is exhibiting an upward trend over time. The manufacturing of glass bottles is costlier in terms of time and resources and is associated with a higher level of heat generation and environmental pollution compared to recycling processes. In response to the aforementioned challenges, companies that use glass bottles need to implement strategies to manage their reverse supply chains in conjunction with their traditional supply chains, as the economic and environmental benefits of returned products are unquestionable. Closed-loop supply chains (CLSCs) integrate forward and reverse flows of products and information. This integration helps companies to have a broader view of the whole chain. Despite these advantages, managing CLSCs can be challenging as they are exposed to many uncertainties regarding supply and demand processes, travel times, and quantity/quality of returned products.In this study, we consider the production planning, inventory management, and vehicle routing decisions of a CLSC of beverage glass bottles. We propose an MILP model and rely on a multi-stage adjustable robust optimization (ARO) formulation to deal with the randomness in both the demand for filled bottles and the requests for pickups of empty bottles. We develop an exact oracle-based algorithm to solve the ARO problem and propose a heuristic search algorithm to reduce the solution time. Our numerical experiments not only show the incompetency of the customary method, namely the affine decision rule approach, but also illustrate how our algorithms can solve the small-size problems and significantly improve the quality of the obtained solution for large problems. Furthermore, our numerical results show that robust plans tend to be sparse, meaning the routes are chosen so that empty bottles are transported to production sites in such a way that fewer new bottles need to be ordered. Thus, robust planning makes the CLSCs more environmentally friendly.