基于改进鲸鱼优化算法的血液供应链网络多目标鲁棒优化设计

为解决血液供应链网络设计中的不确定性问题,建立了一种血液供应链网络多目标鲁棒优化设计模型。首先,针对带有5个节点的血液供应链网络,建立考虑安全库存的、目标为成本最小、存储时间最短的优化函数,并采用ε约束、Pareto最优和鲁棒优化方法对已建模型进行处理,将多目标问题转化为单目标鲁棒问题;其次,对原有鲸鱼优化算法（WOA）进行改进,引入差分算法的交叉和变异理念,增强了搜索能力并改善了局限性,从而得到差分鲸鱼优化算法（DWOA）,并采用此算法对处理后的模型求解。通过数值实例,验证当测试问题相同时,优化模型在需求短缺方面比确定模型的短缺量平均少76%。因此,所提优化模型在应对需求短缺时更具优势;通过仿真对比分析图像,得出DWOA相比WOA、粒子群优化（PSO）算法和遗传算法（GA）中断时间更短并且成本更低。     

两级供应链联合成本三角模糊需求随机过程模型

根据影响两级供应链系统库存控制及决策过程的随机与模糊特性,基于联合成本提出两级供应链三角模糊需求随机过程模型。对两级供应链系统进行研究,给出其联合成本优化模型。针对交货时间和需求率的模糊特性,分情况利用三角模糊函数设计缺货数量模糊模型,基于此对两级供应链联合成本优化模型进行改进,建立三角模糊需求随机过程模型,并给出该模型的求解过程。通过模型参数敏感性实验以及算法对比实验,验证了所提模糊随机过程模型的有效性。     

基于改进智能水滴算法的多目标供应链最优模型

为了最大限度地降低制造型供应链的销售成本并缩短供货时间,提出了一种基于改进智能水滴算法的多目标供应链优化模型。该模型通过在选项选择期间同时考虑成本和时间来提高供应链效率,并能够将制造型供应链中的销售成本和交货时间最小化。通过使用帕累托最优准则对传统的智能水滴算法进行修改,从而得到一个帕累托集,以实现两个目标的最小化。通过3个实例对所提算法进行了测试,并采用世代距离和超区域比指标将其与蚁群优化算法进行了比较。实验结果显示,所提方法的性能更优,生成的解集更接近真实帕累托集,能够覆盖更大的解区域面积,且计算效率较高。     

多周期多原料的供应链网络成本优化及其混合遗传算法

建立并求解一个基于成本最小的供应链网络模型.与以往研究不同,在该模型中生产一种产品需要至少两种原料,每种原料都可以由备选供应商提供.根据模型的特点,用0、1代表对原材料供应商、工厂和分销中心的选择情况,以MATLAB 7.6为平台,运用Sheffield大学的遗传算法工具箱,将遗传算法与线性规划算法相结合,实现了模型的求解.算例结果表明,给出的染色体编码方案正确,混合遗传算法有效,能解决多周期、多原料的供应链网络成本优化问题.还探讨了需求和距离变化,以及需求随机时对最优成本和最优个体的影响.研究表明,需求变化的影响大于距离变化的影响,需求随机对最优成本和最优个体的影响不大.     

随机需求下的供应链库存控制策略研究

考虑了由多个供应商、一个配送中心组成的二级供应链系统在市场需求为随机情况下的多品种库存问题。通过确定各变量之间的关系,以配送中心损失期望值最小为目标函数,建立了一个混合整数非线性规划模型;利用求解多元函数条件极值的办法来求解该问题模型;最后给出了一个算例进一步诠释了该解法,从而丰富了在面对市场为随即需求下的多品种库存控制策略的研究工作。     

考虑质量价值水平的复杂产品供应链质量成本优化方法

优化复杂产品供应链质量成本是提高供应链质量管控能力、降低供应链质量风险的重要方法.综合考虑产品质量水平和产品研制成本,提出复杂产品质量价值概念,并详细分析以供应商网络为基础的复杂产品质量价值形成机理.建立复杂产品质量价值GERT网络模型,实现复杂产品质量价值水平的量化计算,并以此为基础,通过识别网络中的关键供应商建立优化模型,提出考虑质量价值水平的复杂产品供应链质量成本优化方法.最后通过算例验证模型方法的科学性和有效性.     

基于碳交易的已存供应链网络优化研究

针对碳交易环境下的已存供应链物流网络优化问题,提出了一个混合整数线性规划模型。该模型综合考虑了已存工厂/物流中心的关闭或继续开设,新增候选工厂/物流中心,以包含供应链运营成本和碳交易成本在内的总成本最小化为目标。随后设计了数据生成准则,在Java中调用Cplex求解,通过算例验证了模型的有效性和求解方法的可行性。最后灵敏度分析为决策制定者提供了一些有意义的启示：较高的单位碳交易价格将迫使企业增加运营成本以降低实际碳排放量,那些注重碳减排的优秀企业将从碳交易中获得收益;碳排放配额不会对供应链运营产生影响,也不会改变供应链的实际碳排放量,但较低的碳排放配额会增加企业的碳交易成本,从而增加供应链的总成本。     

需求依赖减排水平和价格的供应链决策与协调机制

针对由一个低碳产品制造商与一个零售商组成的供应链, 考虑需求同时受减排水平和销售价格的影响, 分别研究寄售契约、收益共享契约以及收益共享与减排成本共担3 种契约下供应链企业的优化决策, 并进一步探讨当需求的确定部分为和式、随机部分服从均匀分布时的供应链系统的最优决策. 从理论上证明了制造商与零售商之间的合作利于促进减排水平的提升, 也利于供应链系统期望总利润的增加. 最后, 探讨了不同参数对协调供应链绩效的影响.

     

考虑中断风险与模糊定价的闭环供应链网络设计模型

为缓解供应中断对企业的打击,文中提出了在竞争环境下考虑模糊定价和中断风险的双目标闭环供应链网络模型。定义不确定需求为供应链及其竞争对手向客户提供的价格函数,使供应链在竞争环境中实现总利润最大化与碳排放量最小化。文中基于可能性理论求解所提模型,将双目标模型转换为单目标模型,最后使用真实案例进行数值算例分析。结果表明,所提模型不仅可以增强供应链抵御风险的能力,还有助于提高其在市场中的战略地位。     

食品分销网络弹性设计与公平关切行为研究

研究了竞争型供应链弹性网络设计中的行为运作问题,首先建立了集产品制造成本/仓库运营成本/易腐品配送成本/网络节点选择/零售商公平厌恶成本于一体的整体配送框架。利用供应链背景下的一般运作模型,建立了弹性管理下的竞争型多源网络。考虑多源弹性供应网络下各级分销商失效的潜在风险,并分析了零售商公平厌恶下的消极影响。最后考察了一定水平的期望容忍条件、全球供应链和公平关切对于目标函数、正向架构的弹性运作和供应链成员的影响。     

The replenishment policy of agri-products with stochastic demand in integrated agricultural supply chains

Market demand of agri-products is influenced by uncertain factors, such as weather, temperature, and customer preferences. In integrated agricultural supply chains, traditional inventory models are useless because of the stochastic demand and deteriorative characteristic of agri-products. This paper provides a method to determine the optimal replenishment policy of integrated agricultural supply chains with stochastic demand. In these EOQ/EPQ models, shortages are allowed and are backlogged if market demand is stochastic. The objective function is to minimize the total cost of the supply chain in the planning horizon. The total cost includes the ordering cost, the holding cost, the shortage cost and the purchasing cost. Thinking of the nonlinear relationship and dynamic forces in models, a system dynamic (SD) simulation model is constructed to find the optimal lot size and replenishment interval. Finally, an example is given to make a sensitivity analysis of the simulation model. Compared to traditional methods (such as equalize stochastic demand), the total cost decreases by 16.27% if the supply chains adopt the new replenishment policy. The results illustrated that the new replenishment policy (with intelligent method) is beneficial to help supply chain make decision scientifically. Moreover, the intelligent method can simulate stochastic demand perfectly, and it is effectively for solving the complicated and mathematically intractable replenishment problem.     

Blood inventory management: Ordering policies for hospital blood banks under uncertainty

The blood supply chain faces several challenges, such as stochastic demand and supply, the relation between the various stages of the chain, and the intrinsic nature of the product. Blood is a perishable, scarce, and (in most cases) voluntarily supplied product used to perform vital transfusions in patients which increases the pressure of managing its supply chain as efficiently and effectively as possible. For these reasons, it is crucial to have optimized inventory management that allows the availability of the right type of blood product, in the right place, at the right time, and in the right amount while avoiding wastage, especially in hospital blood banks that are the direct link to patients. This work aims to address these challenges with a new two-stage stochastic programming model for defining optimal ordering policies for blood products, considering demand uncertainty. This model minimizes wastage, shortages, and total costs related to blood inventory management, including ABO-substitutions. The model supports hospitals’ tactical-operational decisions of when and how much blood products to order. A case study of a Portuguese hospital is used to validate and show the applicability of the model. By comparing several ordering policies, we show that it is possible to contemplate the decision maker's goals whilst obtaining substantial reductions in terms of wastage and costs. These results allow the definition of an important set of managerial insights.     

具有模糊需求的多商品流供应链网络均衡研究

研究由多个相互竞争的制造商与多个相互竞争的零售商组成,且零售商处面临模糊市场需求、存在差异性的多商品供应链网络均衡问题.运用logit模型刻画消费者的随机选择行为,利用模糊事件的可信性测度推导零售商的模糊期望利润,借助有限维变分不等式理论构建具有模糊需求的多商品流供应链网络均衡状态满足的变分不等式,并分析了供应链网络均衡解的存在性和唯一性.最后,结合算例讨论了需求的模糊性对供应链网络均衡的影响.     

具有风险规避型零售商的闭环供应链网络均衡分析

在随机需求条件下研究了由多个相互竞争的供应商、制造商、零售商和消费市场组成,且零售商具有风险规避特性的再制造闭环供应链网络均衡问题.通过对不同决策层级最优化行为的分析,分别得到各层级和整个供应链网络实现均衡的条件,并建立相关的变分不等式模型.运用拟牛顿算法对变分不等式进行求解,通过仿真分析了随机再制造率和零售商的风险规避程度对网络成员最优行为和闭环供应链网络均衡的影响.     

Modelling inter-supply chain competition with resource limitation and demand disruption

This paper proposes a comprehensive model for studying supply chain versus supply chain competition with resource limitation and demand disruption. We assume that there are supply chains with heterogeneous supply network structures that compete at multiple demand markets. Each supply chain is comprised of internal and external firms. The internal firms are coordinated in production and distribution and share some common but limited resources within the supply chain, whereas the external firms are independent and do not share the internal resources. The supply chain managers strive to develop optimal strategies in terms of production level and resource allocation in maximising their profit while facing competition at the end market. The Cournot–Nash equilibrium of this inter-supply chain competition is formulated as a variational inequality problem. We further study the case when there is demand disruption in the plan-execution phase. In such a case, the managers need to revise their planned strategy in order to maximise their profit with the new demand under disruption and minimise the cost of change. We present a bi-criteria decision-making model for supply chain managers and develop the optimal conditions in equilibrium, which again can be formulated by another variational inequality problem. Numerical examples are presented for illustrative purpose.     

Supply chain network equilibrium with revenue sharing contract under demand disruptions

Contract is a common and effective mechanism for supply chain coordination, which has been studied extensively in recent years. For a supply chain network model, contracts can be used to coordinate it because it is too ideal to obtain the network equilibrium state in practical market competition. In order to achieve equilibrium, we introduce revenue sharing contract into a supply chain network equilibrium model with random demand in this paper. Then, we investigate the influence on this network equilibrium state from demand disruptions caused by unexpected emergencies. When demand disruptions happen, the supply chain network equilibrium state will be broken and change to a new one, so the decision makers need to adjust the contract parameters to achieve the new coordinated state through bargaining. Finally, a numerical example with a sudden demand increase as a result of emergent event is provided for illustrative purposes.     

Two-echelon fuzzy stochastic supply chain for the manufacturer–buyer integrated production–inventory system

This paper deals with two-echelon integrated procurement production model for the manufacturer and the buyer integrated inventory system. The manufacturer procures raw material from outside suppliers (not a part of supply chain) then proceed to convert it as finished product, and finally delivers to the buyer, who faces imprecise and uncertain, called fuzzy random demand of customers. The manufacturer and the buyer work under joint channel, in which a centralized decision maker makes all decisions to optimize the joint total relevant cost (JTRC) of entire supply chain. In this account, in one production cycle of the manufacturer we determine an optimal multi-ordering policy for the buyer. To be part of this, we first derive the JTRC in stochastic framework, and then extend it in fuzzy stochastic environment. In order to scalarize the fuzzy stochastic JTRC, we use an evaluation method wherein randomness is estimated by probabilistic expectation and fuzziness is estimated by possibilistic mean based on possibility evaluation measure. To derive the optimal policies for both parties, an algorithm is proposed. A numerical illustration addresses the situations of paddy procurement, conversion to rice and fulfillment of uncertain demand of rice. Furthermore, sensitivity of parameters is examined to illustrate the model and algorithm.     

3级网状随机性库存控制策略的仿真优化

研究了多制造商,多分销商和多零售商的3级网状随机性库存系统的(r,Q)库存控制策略问题.由于该系统具有顾客到达时间服从泊松分布,随机顾客需求量,随机顾客购买行为,随机订货时间和制造商生产容量有限制等特点,使得解析方法很难描述系统中的多种复杂随机因素并无法求解有效的库存控制策略.为此建立了以总成本最小为目标的数学模型,运用了基于仿真的优化方法,通过将仿真方法与粒子群优化算法相结合对问题进行求解.最后通过仿真实例与比较,验证了模型和基于仿真的粒子群优化方法的可行性和有效性.也表明了基于仿真的优化方法在供应链管理中的适用性.     

考虑供应商选择的选址一库存一路径的联合优化

针对装配型制造企业供应链集成优化问题,建立了随机需求情形下整合供应商选择和各层级之间运输方式选择的多层级选址—库存模型。该模型通过对供应商的选择,装配厂和分销中心的选址,相邻两层级之间的分配服务关系及运输方式的确定,实现整体供应链网络成本最小化。为求解此混合整数非线性规划模型,设计了一种矩阵编码的改进自适应遗传算法。仿真实验表明,该算法的解的寻优能力明显优于标准遗传算法,得出了供应链总成本与装配厂的最大提前期存在一定规律性的结论。