Optimal inventory control policy and supply chain coordination problem with carbon footprint constraints

Carbon footprint constraints exert pressure on supply chains to reexamine decisions. In this paper, we consider carbon transfer cost and carbon holding cost in a supply chain. A multiperiod dynamic programming model with carbon footprint constraints is presented to investigate the impact of carbon transfer cost and carbon holding cost on inventory control policy as well as the supply chain coordination problem. A two‐control limit inventory control policy is proved to be optimal and a contract with wholesale price, subsidy, and fixed setup cost is verified analytically to coordinate the supply chain. Finally, a numerical study is conducted to reveal managerial insights. We find that when the supply chain is coordinated, the chain's profit is more sensitive to carbon transfer cost while inventory level is more sensitive to carbon holding cost. Additionally, because of the complexity of the coordinated contract, when it is not easy to coordinate the supply chain, it is better to keep the values of wholesale price, subsidy, and fixed setup cost below the corresponding values for the coordinated supply chain.     

基于强化学习和半马氏过程的供应链优化

在网络化制造环境下,供应链在地理分布上的分散性、市场需求的随机性都使得供应链的管理越来越复杂。应用强化学习和半马氏过程理论针对跨地区且存在地区生产成本差异的供应链管理问题进行了建模,分析了在随机需求的情况下,供应链的库存决策问题。应用实例说明该方法的可行性和有效性。     

基于库存切换的不确定动态供应链网络系统模糊鲁棒控制

研究基于库存切换的不确定动态供应链网络系统的鲁棒运作问题.首先,建立含有系统参数不确定和顾客需求不确定的动态供应链网络的离散T-S模糊模型;然后,提出一种新的模糊鲁棒控制策略,该控制策略不仅可以有效遏制子系统切换时产生的较大波动,而且可以抑制不确定因素对供应链网络的影响,进而保证供应链网络在不确定环境下鲁棒稳定;最后,通过仿真实例表明了所提出模糊鲁棒控制策略的有效性.     

Coordination-based inventory management for deteriorating items in a two-echelon supply chain with profit sharing

This study develops a model for inventory management consisting of a two-echelon supply chain (SC) with profit sharing and deteriorating items. The retailer and the supplier act as the leader and follower, in which the supplier faces a huge setup cost and economic order quantity ordering strategy. The market demand is affected by the sale price of the product, and the inventory has a deterioration rate following a Weibull distribution. The retailer executes three profit-sharing mechanisms to motivate the supplier to participate in SC optimisation and to extend the life cycle of the product. A search algorithm is developed to determine the solutions as using the profit-sharing mechanisms. The outcomes from numerical experiments demonstrate the profitability of the proposed model.     

A simulation-based genetic algorithm for inventory optimization in a serial supply chain

One of the important aspects of supply chain management is inventory management because the cost of inventories in a supply chain accounts for about 30% of the value of the product. The main focus of this work is to study the performance of a single‐product serial supply chain operating with a base‐stock policy and to optimize the inventory (i.e. base stock) levels in the supply chain so as to minimize the total supply chain cost (TSCC), comprising holding and shortage costs at all the installations in the supply chain. A genetic algorithm (GA) is proposed to optimize the base‐stock levels with the objective of minimizing the sum of holding and shortage costs in the entire supply chain. Simulation is used to evaluate the base‐stock levels generated by the GA. The proposed GA is evaluated with the consideration of a variety of supply chain settings in order to test for its robustness of performance across different supply chain scenarios. The effectiveness of the proposed GA (in terms of generating base‐stock levels with minimum TSCC) is compared with that of a random search procedure. In addition, optimal base‐stock levels are obtained through complete enumeration of the solution space and compared with those yielded by the GA. It is found that the solutions generated by the proposed GA do not significantly differ from the optimal solution obtained through complete enumeration for different supply chain settings, thereby showing the effectiveness of the proposed GA.     

随机需求下双渠道供应链库存动态交互优化

针对双渠道供应链库存系统导致的缺货与库存积压等问题，在线上线下均为随机需求的条件下，考虑生产延迟和物流延迟，建立了双渠道库存的单独控制、集中控制和交叉补货控制这三种模式的动态优化模型。首先，以库存动态微分方程为基础，创新性地以控制理论为指导思想，以泰勒展开和拉普拉斯变换为手段，得到双渠道库存系统的反馈传递函数；其次，考虑了交叉补货的进销存过程中的周期间交互、上下游间交互以及渠道间交互，利用延迟控制、反馈控制和比例-积分-微分（PID）控制构造了双输入、双输出的复杂交互系统，以此寻求双渠道库存系统自身以及渠道间的动态供需双平衡，优化双渠道库存持有量，降低缺货次数和缺货量并使其保持动态稳定状态；最后，通过数值仿真实验，对比三种双渠道库存控制策略。仿真结果表明，在线上线下渠道为不同分布的随机需求时，交叉补货控制的剩余库存比独立库存控制降低了4.9%，交叉补货控制的缺货率与独立控制和集中控制相比分别下降了66.7%和60%。实验结果表明，在线上线下渠道为不同分布的随机需求的情况下使用双渠道交叉补货策略能很好地降低库存持有量，减少缺货次数和缺货量，从而节约库存成本。     

Simultaneous control of vehicle routing and inventory for dynamic inbound supply chain

This paper investigates inbound logistics for an OEM (Original Equipment Manufacturing) manufacturer, who aims at short production time and JIT policy. In such a case, it can be argued that the inbound vehicle routing schedule should be combined with incoming parts inventory control. In this paper, we propose a simultaneous control method of combining vehicle scheduling and inventory control for such dynamic inbound logistics. For the transportation control, a vehicle routing system, in which delivery jobs are made with shipments of one supplier, is proposed to generate a vehicle routes plan by considering production start time, travel time, waiting time, and loading/unloading time. To evaluate the performance of the generated vehicle routing plan, a goal model is also developed by considering vehicle operating cost, stock level exceeding penalty, and transportation efficiency. A generated vehicle routing plan can be rejected when the stock level is over the capacity and an appropriate number of vehicles for its manufacturing environment can be determined. Using real data from an LCD firm, a simulation study is conducted. The simulation results indicate that the simultaneous control approach requires fewer vehicles than the existing system and shows better efficiency of transportation. This method can also be used to determine the appropriate incoming part inventory level or the number of vehicles required in dynamic inbound logistics.     

闭环供应链混合切换库存控制模型研究

针对一类具有回收、再制造、再分销的闭环供应链系统,以再制造产品的补货能力为切换信号设计了基于再制造优先的混合切换库存控制策略,使得市场需求优先由再制造产品满足,并应用切换控制理论研究混合切换库存控制策略的性能特征,分析系统参数对闭环供应链系统的关键性能指标的影响。仿真分析表明,合理的切换控制策略可以有效抑制闭环供应链运作过程的波动,保证系统具有良好的“牛鞭效应”特征、平稳的库存管理成本以及较高的顾客服务水平。     

供应链存储系统无线射频识别使能的定量在制品法控制策略仿真

无线射频识别(radio frequency identification,RFID)技术的出现为库存控制策略的创新提供了一条有效的途径.本文利用RFID技术,将原有单个制造系统的流通卡系统推广到供应链的多级库存网络中,设计了RFID使能的电子流通卡系统.基于电子流通卡,实现了RFID使能的定量在制品法(constant work-in-process,CONWIP)控制策略;并建立了CONWIP控制策略的分销网络模型.为比较和验证CONWIP控制策略性能,开发了三级分销网络仿真系统,使用该系统,将其与RFID使能的(r,Q)策略进行比较,验证了CONWIP策略在一定条件下,能够有效降低存储成本、提高服务水平.     

供应链中控制多级存储的射频辨识Push/Pull混合策略设计与仿真

由于射频辨识(radio frequency identification,RFID)激励的电子看板系统能够从远端看见供应链节点企业库存的状况,使得广域分布的供应链多级存储能够实现RFID激励的Pull控制.本文根据供应链分销网络多级存储的结构特点,以及系统运作期间各阶段节点企业的功能,在不同阶段采用不同的控制策略.因此,设计了多种不同的RFID激励的Push/Pull混合控制策略.为了比较和验证各混合策略对多级存储的控制性能,建立了以总库存成本、总缺货损失、总运行成本和库存周转率作为评价策略性能的指标体系.由于供应链系统的动态性与随机性,难以进行数学建模和精确求解,因此基于离散事件系统仿真原理,设计并实现了仿真模型.通过对各策略下多种结构的供应链分销网络多级存储的仿真,验证并分析了制造商阶段采用Push控制,分销商和零售商阶段采用Pull控制的策略的有效性和最优性.     

含时滞的不确定性供应链网络系统牛鞭效应控制策略及其经济性能分析

考虑需求、生产能力、供应链结构等内外不确定性因素和供应链系统运作延迟,构建了不确定环境下含时滞的供应链库存网络系统状态转移模型.针对牛鞭效应问题,提出了基于库存水平波动状态的控制策略和相应的经济性能指标;借助线性矩阵不等式方法,深入分析库存策略的参数优化设计对牛鞭效应以及经济性能的影响.仿真结果表明,在经济性能约束下,该库存策略具有较强的牛鞭效应遏制能力,从而表明了策略的有效性和实用性.     

信息共享受限条件下的供应链网络系统牛鞭效应控制策略

研究在信息共享受限条件下供应链网络库存系统的牛鞭效应控制问题,建立了包括市场需求、信息可获得性、信息及时性等不确定性因素的库存网络系统状态转移模型,从系统内部动力学机制的角度分析了牛鞭效应的成因,提出了动态库存控制策略,并给出了策略参数设计的线性矩阵不等式组算法.运用系统稳定性理论,深入分析了信息共享对牛鞭效应的影响,并通过仿真结果验证了库存控制策略的有效性和实用性.     

An integrated supply chain model for new products with imprecise production and supply under scenario dependent fuzzy random demand

In the present day business scenario, instant changes in market demand, different source of materials and manufacturing technologies force many companies to change their supply chain planning in order to tackle the real-world uncertainty. The purpose of this paper is to develop a multi-objective two-stage stochastic programming supply chain model that incorporates imprecise production rate and supplier capacity under scenario dependent fuzzy random demand associated with new product supply chains. The objectives are to maximise the supply chain profit, achieve desired service level and minimise financial risk. The proposed model allows simultaneous determination of optimum supply chain design, procurement and production quantities across the different plants, and trade-offs between inventory and transportation modes for both inbound and outbound logistics. Analogous to chance constraints, we have used the possibility measure to quantify the demand uncertainties and the model is solved using fuzzy linear programming approach. An illustration is presented to demonstrate the effectiveness of the proposed model. Sensitivity analysis is performed for maximisation of the supply chain profit with respect to different confidence level of service, risk and possibility measure. It is found that when one considers the service level and risk as robustness measure the variability in profit reduces.