煤炭企业发行碳债券可行性研究——以某大型一体化经营煤企为例

煤市的持续低迷给煤企转型升级发展带来资金压力,筹集低成本资金成为煤企共同夙求,今年国内首单成功发行的碳债券,正是为绿色转型发展的煤企打开了一条全新的融资思路和渠道,研究碳债券的发行机制和复制推广效应成为重要而有意义的事情。通过对碳资产、碳交易市场,以及碳债券浮动利率形成机制、碳交易价格设定机制等关键环节的全面摸底,以某大型国有煤炭企业为例,分析了碳债券发行的成本收益测算、风险评估、发行流程等问题,并据此给出发行建议,对于启发煤企以碳债券为起点,积累碳资产收益转化经验,推动集团实现碳资产经济收益与社会引领示范效益,具有参考意义。     

冷链品配送系统双目标优化研究——基于多温共配的比较研究

本文在传统配送模型基础上，以蓄冷式多温共配与机械式多温共配模式为研究对象，综合考虑配送系统中的车辆成本、配送中心运行成本、保鲜制冷、保温箱等相关费用，建立成本最小化与客户满意最大化双目标函数，并设计优化配送的 NSGA - 算法。最后，本文通过实际算例对两种模式的有效性进行验证，对不同模式产生的系统成本以及客户满意度进行对比分析，从而论证了蓄冷式多温共配模式的理论支持性与实践支撑性。     

碳税与碳交易机制下基于演化博弈模型的钢铁企业碳减排投资决策分析

碳税和碳交易作为政府调控碳减排目标的主要措施之一,会对钢铁企业的碳减排投资决策产生重要影响。构建钢铁企业碳减排投资决策的演化博弈模型,并分别探讨在碳税和碳交易机制下企业碳减排投资策略。结果表明,碳减排投资的效率和成本以及搭便车收益对于钢铁企业的策略选择有重要影响;碳税和碳交易机制均能通过碳定价的方式降低搭便车行为的概率,促进钢铁企业协同减排,但二者对于企业收益的影响存在差别。     

试论大区公司集中库存管理——对中国石油成品油供应链管理模式的探索

当前中国石油的成品油配送体系仍然停留在要货制上。炼化企业、大区公司和省区公司由于各自的库存控制策略不同,存在“牛鞭效应”,容易导致需求放大、库存偏高。组织流、信息流、物流不畅是导致供应链库存不当的主要原因,实行大区公司集中库存管理可以有效地解决这个问题。这种管理模式体现了供应链集成化管理的思想,突破了传统的“库存拥有者管理库存”的禁锢,由大区公司作为上下游企业的沟通和联系桥梁,并对成品油的生产、流通和库存进行管理和控制。大区公司集中库存管理是一种以信息化为基础的过程管理,它可以使各企业集中优势资源做好自己擅长的业务,通过信息共享提高决策效果,实现成品油的自动配送补货以及整个系统运营的优化。为此,须建立统一的编码系统、市场销售信息库、物流调度指挥系统、库存信息共享机制、成品油配送成本管理系统以及供应链协调管理机制等。     

润滑油品集中仓储配送模式在煤化工企业的应用

针对煤化工企业采用传统润滑油品分散仓储模式带来的现场需建设多个润滑站、油品库存量大、油品储存质量及现场加换油质量得不到保障等问题，引进润滑油品集中仓储配送模式，砍掉现场润滑站这个中间环节。实践表明，润滑油品集中仓储配送模式可以免去现场润滑站建设成本，降低油品库存成本，提升设备润滑可靠性。     

碳交易的机遇与挑战

碳市场的有效性、流动性和稳定性取决于合理的定价机制,使价格能够反映真实的碳排放边际减排成本、综合社会成本与外部性成本。2020年9月,在第七十五届联合国大会上,中国承诺二氧化碳排放要在2030年前达到峰值、2060年前实现碳中和。碳减排是一项艰巨复杂的工作,需要各方共同努力。碳交易是实现碳减排的重要经济手段,也是我国实现“双碳”目标的重要路径。     

《巴黎协定》对油气行业发展的影响

《巴黎协定》已于2016年11月4日生效,控温2摄氏度将使全球近2/3化石能源储量得不到开发,导致油气上游投资大幅减少,对油气公司融资造成阻碍.随着缔约国碳约束逐步增强,油气公司将被要求做出碳财务披露,中国公司海外项目运营难度加大.国际石油公司纷纷探寻低碳转型之路,引入碳定价机制,将碳成本纳入项目投资计划,加大天然气和新能源业务投资比重.2017年,中国碳交易市场将全面铺开,石化、化工企业将被首批纳入碳配额体系.建议中国石油行业高度重视《巴黎协定》的影响和碳排放权的价值,制定低碳发展战略;各石油公司逐步建立碳资产管理体系;将碳成本纳入项目投资决策,以节能管理促进碳减排;积极参与电力和船舶行业的碳标准制定,建立碳交易能力.     

低碳背景下我国碳排放权市场价格的影响因素分析

以2014—2018年广东省碳交易价格作为研究对象,研究了广东省碳交易价格的影响因素。研究发现,广东碳市场的建立已经产生了一定的减排成效,企业发电成本、当地用电量都会左右碳价格的走势,欧洲CER期货价格依然是影响广东省碳交易价格的最显著性因素,同时,上海银行间同业拆放利率以及国际天然气价格等都对广东省碳排放权交易价格存在正向影响。基于此,我国应该继续推进碳市场建设、积极调整能源结构,巩固减排效果,同时关注国际碳排放价格走势,提前做好能源价格预测,掌握能源价格走势,衡量碳减排成本与能耗成本之间的差异,找到能源选择与节能减排间的平衡点。     

我国碳排放权交易价格影响因素分析

本文通过选取我国7 家碳交易试点公布的碳交易价格为样本， 利用 EEMD 方法将碳交易价格分解， 并运用 FGLS 分析各影响因子对碳价的影响程度。 研究结果表明： 碳排放权交易价格受到市场内在机制以及市场外部环境双重作用的影响； 市场内在机制下， 能源价格与碳排放权交易价格之间相互作用相互影响， 其中石油价格对碳排放权交易价格影响最大； 市场外部环境下， 各地区发展的季度GDP 增长率、 气温以及降水量均对碳排放权交易价格有着不同程度的影响。     

库存控制之供应链多目标视角下的应用研究——以工业润滑油供应链为例

供应链环境下库存控制的研究已经成为趋势,区别于常规的单目标库存控制的研究,本文以工业润滑油供应链为依托,提出了在供应链背景下考虑供应链库存成本最小化和客户平均需求满足率最大化为目标的库存控制研究思路,构建了多目标库存控制模型。最后将所建的供应链视角下多目标库存控制决策模型进行实证分析,为目标供应链上的企业做出生产、销售等决策提供依据。     

Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach

This paper proposes a two-stage multiple criteria dynamic programming approach for two of the most critical tasks in supply chain management, namely, supplier selection and order allocation. In the first stage, to address multiple decision criteria in supplier ranking, the analytic hierarchy process (AHP) is employed. In the second stage, supplier ranks are fed into an order allocation model that aims at maximizing a utility function for the firm as well as minimizing the total supply chain costs, subject to constraints on demand, capacity, and inventory levels. A dynamic programming approach is crafted to solve the proposed bi-objective model.     

Setting operating policies for supply hubs

This paper deals with the joint management of operations at the supply hub for the customer and the upstream supplier. Different operating conditions are considered, namely, backordering, minimum and maximum specified inventory levels. Some analytical insights on better managing suppliers operating under a vendor managed inventory program are presented. Essentially, we show that the penalty cost imposed on over- and under-stocking, and the min–max policy for hub inventory reside in the power of the hub operator. The relationship between supply hub policy and performance measures is quite complex and non-linear in nature. We suggest a structured hierarchical approach which can help supply hub in achieving balance between various parties involved in chain. A numerical example and an algorithm are included to highlight this result.     

Inventory service-level optimization within distribution network design problem

We propose a sequential heuristic approach to optimize inventory service levels in a two-stage supply chain. The proposed approach deals with service level and inventory decisions, simultaneously with network design decisions, and incorporating unfulfilled demand costs in a previous inventory-location model. A two-step formulation is considered, where the first step optimizes service level and the second step addresses location and inventory decisions. Each algorithm iteration solves an inventory-location model for a fixed service level, and then the service level is updated in order to reach an equilibrium condition between operating system and unfulfilled demand costs. The algorithm converged in three iterations for a set of sample instances, obtaining the same outcome in comparison with a more intuitive, exact, but more time-consuming search procedure.     

Inventory control in a two-echelon dual-channel supply chain with setup of production and delivery

This paper considers a two-echelon dual-channel supply chain model with setup of production and delivery and develops a new inventory control policy for the supply chain. Previously, a two-echelon supply chain model without setup of production and delivery is considered and a one-for-one inventory control policy is applied to the supply chain. In the inventory control policy, production is stopped when the warehouse inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. Moreover, delivery to the retailer is stopped when the store inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. The total cost that consists of inventory holding costs and lost sales cost is considered, and setup costs are not considered in the total cost. Once setup costs are introduced, the one-for-one inventory control policy is no longer appropriate. Then, this paper develops a new control policy for the two-echelon dual-channel supply chain with setup of production and delivery. As performance measure, the total cost that consists of inventory holding costs, lost sales cost, and production and delivery setup costs is considered, and the total cost calculated on the basis of Markov analysis demonstrates the effectiveness of the proposed control policy.     

政府补贴下的三级低碳供应链减排博弈研究

本文分别构建了政府补贴下，供应链上企业单独减排、供应商对制造商碳减排成本进行分担、供应商和零售商均对制造商碳减排成本进行分担3种减排模型，求解得到不同减排模式下，包括成本分担率和单位减排量在内的供应链最优决策。研究发现，政府补贴率的提升反而使成本分担率降低。通过博弈分析及算例验证得出：在供应链上三方企业联合减排下，即供应商和零售商都对制造商的碳减排研发提供资金支持时，单位产品的减排量及各企业利润达到最大，仅供应商对制造商碳减排成本分担时次之， 供应链上企业单独减排时最小， 但仅供应商一方对制造商的碳减排成本进行分担时的成本分担率，比其与零售商同时分担时的要大。这些结论为政府确立合适的补贴方案及供应链上企业减排策略的制定提供了理论依据。     

Production capacity planning for multiple products under uncertain demand conditions

This study chiefly deliberates issues regarding capacity allocation for multiple products. When producing multiple products, a manufacturer needs to allocate a favorable production quantity to each product under conditions of uncertain demand since the excess or shortage of a product will in turn cause the loss of profit. The proposed model and the corresponding algorithm in this study are used to find out the optimal capacity allocation under the given probability density function of specific demands and to effectively allocate limited capacity to multiple products with an aim to maximize profit. Finally, the numerical example suggests that the marginal profit, the inventory holding cost, the shortage cost, the loss of excess production, and market demands should be considered in an effort to discover an optimal capacity allocation with regard to multiple products.     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

Evaluation of 4PL operating models: A decision making approach based on 2-additive Choquet integral

By being a supply chain integrator who can assemble and manage the resources, capabilities, and technology of its own organization with those of complementary service providers, fourth party logistics (4PL) providers deliver comprehensive supply chain solutions and form an important option for business outsourcing. The adequate design of the partnership between companies in this type of outsourcing activities is essential. In order to support the effective usage of 4PL services, this paper proposes an analytical multiple criteria decision making approach to evaluate 4PL operating models. While decision criteria and their hierarchy were identified, it is observed that there exist interactions, e.g. simultaneous satisfaction of two or criteria is sometimes required. This situation can not be handled with traditional multi-criteria decision making methods which assume criteria independence. 2-additive Choquet integral is appropriate to model criteria interactions by pairs and is used in this study. The proposed framework is applied for a logistics company willing to expand its operations. Finally, an application is provided to demonstrate the potential of the methodology for 4PL operating model selection.     

Streamlining inventory flows with time discounts to improve the profits of a decentralized supply chain

We consider a decentralized supply chain, whereby a supplier sells a product to a group of independent buyers, and develop a strategy for the supplier to offer an all-units price discount or cash rebate for orders that are synchronized with its replenishments. As synchronized orders can be met with inventory directly from receiving to shipping without warehousing, the proposed strategy streamlines system inventory flows to minimize inventory and, hence, the related costs. On the other hand, by increasing the replenishment interval of the supplier, the proposed strategy is able to induce buyers to order in large quantities and hence achieve the objectives of quantity discounts. We show that the proposed strategy can achieve nearly optimal (minimum) system cost, and is much more effective than the existing coordination strategies for decentralized supply chains in the literature.     

Integrated safety stock optimization for multiple sourced stockpoints facing variable demand and lead time

The safety stock placement problem of a multi-stage supply chain comprising multiple sourced stockpoints is addressed in this paper. Each stockpoint faces variability in its downstream demand and suppliers' lead time. The maximum among these suppliers' lead time is determined by employing concepts of order statistics. It is required to find the fill rate and safety stocks at each stockpoint that leads to satisfying the end customer service level at minimum safety stock placement cost. Hence, the fill rates and the safety amounts are decided from a global supply chain perspective. Two models are proposed; a decentralized safety stock placement model and a centralized consolidation model. The decentralized model finds the safety amounts at each stockpoint required to face its underlying lead time demand variability. The consolidation model finds the consolidated safety amounts that will be kept in the relevant consolidation center at each stage. A Benders decomposition technique is developed to handle the nonlinearity and binary restrictions involved in the safety stock consolidation model. Strategies proposed by the consolidation model achieve 45.2-62% reduction in safety amounts that results in a cost savings ranging between 22.2-44.2% as compared to the strategies proposed by the decentralized model.