The impact of forecasting model selection on the value of information sharing in a supply chain

This paper presents a study on the impact of forecasting model selection on the value of information sharing in a supply chain with one capacitated supplier and multiple retailers. Using a computer simulation model, this study examines demand forecasting and inventory replenishment decisions by the retailers, and production decisions by the supplier under different demand patterns and capacity tightness. Analyses of the simulation output indicate that the selection of the forecasting model significantly influences the performance of the supply chain and the value of information sharing. Furthermore, demand patterns faced by retailers and capacity tightness faced by the supplier also significantly influence the value of information sharing. The result also shows that substantial cost savings can be realized through information sharing and thus help to motivate trading partners to share information in the supply chain. The findings can also help supply chain managers select suitable forecasting models to improve supply chain performance.     

乡村产业振兴“基地+农户”同创共享绿色供应链反馈仿真分析

针对养殖企业沼气沼肥供应链不可持续,产生二次污染严重影响生态环境,且农民增收乏力,乡村产业振兴难以推进现状,本文围绕生猪养殖业,并以南昌大学系统工程科研教学基地明鑫农场及周边亟待振兴的农户为例,提出构建"基地+农户"同创共享绿色供应链系统,运用系统动力学方法建立仿真模型,计算反馈环个数;然后结合仿真、反馈环及延迟三组合分析法,从社会效益、环境效益和经济效益三方面对该绿色供应链系统的振兴效益进行反馈仿真分析,并提出相应管理对策,为我国乡村产业振兴提供实践道路.     

Matching product architecture with supply chain design

Product architecture is typically established in the early stages of the product development (PD) cycle. Depending on the type of architecture selected, product design, manufacturing processes, and ultimately supply chain configuration are all significantly affected. Therefore, it is important to integrate product architecture decisions with manufacturing and supply chain decisions during the early stage of the product development. In this paper, we present a multi-objective optimization framework for matching product architecture strategy to supply chain design. In contrast to the existing operations management literature, we incorporate the compatibility between the supply chain partners into our model to ensure the long term viability of the supply chain. Since much of the supplier related information may be very subjective in nature during the early stages of PD, we use fuzzy logic to compute the compatibility index of a supplier. The optimization model is formulated as a weighted goal programming (GP) model with two objectives: minimization of total supply chain costs, and maximization of total supply chain compatibility index. The GP model is solved by using genetic algorithm. We present case examples for two different products to demonstrate the model’s efficacy, and present several managerial implications that evolved from this study.     

产能限制下单向替代产品供应链生产、订货与定价研究

考虑一个产能受限的制造商和一个零售商组成的二级供应链上供需双方信息不完全对称的情景,研究具有单向替代的两种产品生产、订货及响应性定价的供应链决策问题,把问题建立成一个三阶段博弈模型。理论分析得出不同条件下制造商的最优产量及零售商的最优订货和定价决策。通过算例验证了供应链上的最优决策及其条件,灵敏度分析表明制造商产能、潜在市场需求及其方差、替代品的价格敏感系数在一定范围内增大有利于供应链系统及各成员利润增加,被替代产品的价格敏感系数增大可能会导致供应链及制造商利润下降。     

产能约束对闭环供应链回收渠道选择的影响

在制造商存在产能约束下,建立了再制造闭环供应链回收渠道决策的Stackelberg博弈模型,得出了三种回收渠道下的回收率、零售价以及制造商、零售商和供应链的利润,分析了制造商的生产能力对回收渠道决策的影响。研究表明:存在产能约束时,制造商回收渠道中的回收率总是最高的,这与无产能约束时零售商回收渠道中回收率最高的情况明显不同;同时,若废旧产品回收转移支付价格较低,制造商会选择自己回收,此时的零售价最低,制造商、零售商和供应链利润最高;若回收转移支付价格较高,制造商会选择零售商回收,此时的零售价最低,制造商和供应链利润最高。     

Simultaneous engineering approach to an integrated design and process planning

To support integration of design and process planning, a reference model has been developed. This reference model represents the basis for a new methodology for integrated design and process planning which enables a Simultaneous Engineering approach in the early stages of product development. The reference model consists of four partial models. These are the activity model, the information model, the technical system model and the model of integrating methods. Using these models, the methodology enables a concurrent processing of design and process planning activities with regard to different components of a product. Furthermore, the methodology covers planning methods as well as execution methods, to support early transmission of information to downstream activities and a feedback of information to upstream activities within the process chain of design and process planning.     

Production capacity buildup and double marginalization mitigation in a dynamic supply chain

The paper investigates the extent to which capacity investment considerations interact with the double marginalization effect in a simple supply chain governed by a wholesale price contract. To do so, a non-cooperative differential game model is formulated to study the pricing and capacity investment decisions in a supply chain, which consists of a supplier and a manufacturer. In such a game, there are different decision rules—open-loop, closed-loop, feedback—that are available to the supply chain participants, depending on the observability of the current state of the supply chain. While closed-loop and feedback equilibrium strategies involve the observability of other chain member’s production capacity, open-loop equilibrium strategies do not have such requirement. We examine how the supplier and the manufacturer determine, with the different decision rules, their production capacities and pricing policies to maximize their profits over an infinite planning horizon, and determine how the observability of other supply chain’s members’ production capacity affects the magnitude of the double marginalization effect. Our study suggests that the observability of other chain member’s current production capacity entails a lower production efficiency that results in a greater double marginalization effect. This allows us to conclude that observability of other chain member’s current production capacity is associated with a greater double marginalization effect.     

Coordination mechanism for capacity reservation by considering production time,production rate and order quantity

In this paper we study the coordination of a dyadic supply chain producing a high-tech product by contracts. The product has a short life cycle and the buyer faces stochastic demands during the selling period. We consider the production time, which causes the inventory costs on supplier’s side. As the supplier builds production capacity in advance, the production rate is limited to the capacity created during the production time. In addition, we take into account the inventory cost and operational cost for the buyer. We examine the model under both full information and partial information updating situations, and propose a coordinating contract for each case. Our analysis includes the study of members’ decisions under both forced and voluntary compliance regimes. Numerical results are presented to provide more insights into the models developed and the mechanisms proposed.     

考虑决策者失望规避的供应链协同绿色创新动态优化与协调研究

针对决策者存在失望规避行为且产品绿色水平具有动态变化特征的情形,基于失望理论,运用微分博弈的方法研究了供应链协同绿色创新动态优化与协调问题,探讨了供应链成员失望规避程度对绿色创新决策及供应链绩效的影响,并提出双向成本分担契约对供应链进行协调。结果表明,供应链成员是否选择协同绿色创新及产品的绿色水平均与成员的失望规避程度密切相关;分散式决策下,若制造商选择分担供应商部分绿色创新成本,其分担比例与制造商失望规避程度负相关,与供应商失望规避程度正相关;集中式决策下,产品绿色水平、成员绿色创新水平及效用现值均高于协调前分散系统中的对应值;在一定条件下,双向成本分担契约的设计与实施,能有效提升供应链成员效用现值,实现供应链协调。     

Development of a new approach for deterministic supply chain network design

This paper proposes a mixed integer linear programming model and solution algorithm for solving supply chain network design problems in deterministic, multi-commodity, single-period contexts. The strategic level of supply chain planning and tactical level planning of supply chain are aggregated to propose an integrated model. The model integrates location and capacity choices for suppliers, plants and warehouses selection, product range assignment and production flows. The open-or-close decisions for the facilities are binary decision variables and the production and transportation flow decisions are continuous decision variables. Consequently, this problem is a binary mixed integer linear programming problem. In this paper, a modified version of Benders’ decomposition is proposed to solve the model. The most difficulty associated with the Benders’ decomposition is the solution of master problem, as in many real-life problems the model will be NP-hard and very time consuming. In the proposed procedure, the master problem will be developed using the surrogate constraints. We show that the main constraints of the master problem can be replaced by the strongest surrogate constraint. The generated problem with the strongest surrogate constraint is a valid relaxation of the main problem. Furthermore, a near-optimal initial solution is generated for a reduction in the number of iterations.     

Revenue management for a supply chain with two streams of customers

In this paper, we consider revenue management for a service supply chain with one supplier and one retailer. The supplier has a limited capacity of a perishable product and both the supplier and the retailer face customers. Each customer may choose to buy a product from either the supplier or the retailer by considering prices and the cost associated with switching. For the centralized model, the supplier determines the selling prices for both herself and the retailer, and the retailer simply collects a commission fee for each product sold. We derive monotone properties for the revenue functions and pricing strategies. Further, we show that the commission fee increases the retailer’s price while decreasing the supplier’s and leads to efficiency loss of the chain. For the decentralized decision-making model, the supplier and the retailer compete in price over time. Two models are considered. In the first, the retailer buys products from the supplier before the selling season and in the second the retailer shares products with the supplier in retailing. For both models, we discuss the existence of the equilibrium and characterize the optimal decisions. Numerical results are presented to illustrate properties of the models and to compare the supply chain performance between the centralized and the decentralized models.     

北京城市水资源供需系统研究

在研究北京市水资源供需现状的基础上,采用系统动力学方法构建了城市水资源供需模型.利用系统思考中学习型组织的信息反馈回路模式,引入基于可持续发展系统生存回路的水资源供需平衡指标,采用反映供需关系紧张的水供需一次、二次平衡作为衡量地区水危机的变量.按照人口增长与人均综合用水定额不同组合下的城市水需求总量,得到未来北京市水资源供需平衡变化的四种情境,通过动态模拟,分析不同情况下满足水需求的供应方案.结果显示,北京市现有的水资源条件与城市发展需水要求还有较大距离,应在挖掘本地水资源的基础上,依靠南水北调工程等境外调水,解决地区缺水的矛盾.     

A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling

Due to the implementation of government legislation, social responsibility, environmental concern, economic benefits and customer awareness the industries are under a great pressure not only to provide environmentally friendly products but also to take back the product after its use. The issue in reverse logistics is to take back the used products, either under warranty or at the end of use or at the end of lease, so that the products or its parts are appropriately disposed, recycled, reused or remanufactured. In order to overcome this issue, it is necessary to setup a logistics network for arising goods flow from end users to manufacturers. In this study, the optimum usage of secondary lead recovered from the spent lead–acid batteries for producing new battery is presented. The disposal in surface or sewage water or land of liquid content of the lead–acid batteries is strictly restricted. Because of the need for environmental protection and the lack of considerable lead resources, the spent batteries treatment and lead recovery are becoming crucial now-a-days. The objective of this paper is to develop a multi echelon, multi period, multi product closed loop supply chain network model for product returns and the decisions are made regarding material procurement, production, distribution, recycling and disposal. The proposed heuristics based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model (MILP). Finally the computational results obtained through GA are compared with the solutions obtained by GAMS optimization software. The solution reveals that the proposed methodology performs very well in terms of both quality of solutions obtained and computational time.     

What are causes of cash flow bullwhip effect in centralized and decentralized supply chains?

Bullwhip effect in supply chain is a phenomenon which can emerge in both inventory levels and replenishment orders. Bullwhip effect causes variations in cash conversion cycle (CCC) across cash flow of supply chain. As a result, it can lead to inefficiencies such as cash flow bullwhip (CFB). Due to negative impact of CFB on cash flow of supply chain, it can lead to a decrease in efficiency of supply chain management (SCM). That is why supply chain modeling is a proper start point for effective management and control of the CFB. This paper aims to analyze concurrent impact of causes of inventory bullwhip effect and effect of their interactions on CFB based on generalized OUT policy from aspect of CCC variance. To this end, first we develop system dynamics structure of beer distribution game as simulation model which includes multi-stage supply chain under both centralized and decentralized supply chains. Then, in order to develop CFB function, we design experiments in developed simulation model using response surface methodology (RSM). Results demonstrate that if each chain member uses generalized OUT policy as replenishment model, there still exists CFB in both chains and CFB largely stems from rationing and shortage gaming in both centralized and decentralized supply chain. In addition, when information on ordering parameters are not shared among members, parameters of downstream stage (i.e. retailer) are more important than parameters of upstream stage (i.e. manufacturer) in reducing CFB function.     

Optimal design of the auto parts supply chain for JIT operations: Sequential bifurcation factor screening and multi-response surface methodology

This research proposes a solution framework based on discrete-event simulation, sequential bifurcation (SB) and response surface methodology (RSM) to address a multi-response optimization problem inherent in an auto parts supply chain. The objective is to identify the most efficient operating setting that would maximize the logistics performance after the expansion of the assembly plant’s capacity due to market growth. In the proposed framework, we first construct a comprehensive simulation as a platform to model the physical flow of the auto parts operations. We then apply the SB to identify the most important factors that influence system performance. To determine the optimal levels of these key factors, we employ RSM to develop metamodels that best describe the relationship between key decision variables and the multiple system responses. We adapt the Derringer–Suich’s desirability function to find the optimal solution of the metamodels. Computational study shows that our method enables the greatest improvement on system performance. The proposed method helps the case firm develop insights into system dynamics and to optimize the operating condition. It realizes the performance objective of the auto parts supply chain without the need for additional fiscal investment.     

Research on a scheduling mechanism in a complex system based on TOC

Under the condition where there is no seasonal demand fluctuation, short life cycle product supply chain should confront the market environment such as the decreasing of product value, the launch of substitutes and the appearance of competitors’ similar products, and the supply chain will become a very complex system. In this paper, the authors consider a TOC-based scheduling mechanism in this complex supply chain system. under the constant total production cost, it is more important to improve the availability of the wanted product in order to enhance the overall supply chain competitiveness so to obtain more effective output(profit rate) for the supply chain in a long period. Especially we try to apply the SDBR concept into a schedule mechanism in a particular supply chain system, and use numerical analysis to test the efficiency of the proposed method.     

Complexity analysis of dynamic noncooperative game models for closed-loop supply chain with product recovery

In this paper, we consider a closed-loop supply chain (CLSC) with product recovery, which is composed of one manufacturer and one retailer. The retailer is in charge of recollecting and the manufacturer is responsible for product recovery. The system can be regarded as a coupling dynamics of the forward and reverse supply chain. Under different decision criteria, two noncooperative game models: Stackelberg game model and peer-to-peer game model are developed. The dynamic phenomena, such as the bifurcation, chaos and sensitivity to initial values are analyzed through bifurcation diagrams and the largest Lyapunov exponent (LLE). The influences of decision parameters on the complex nonlinear dynamics behaviors of the two models are further analyzed by comparing parameter basin plots, and the results show that with the improvement of retailer’s competitive position, the CLSC system will be more easier to enter into chaos.     

A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler’s demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method.     

Bullwhip effect in a supply chain model with multiple delivery delays

We develop a model of differential equations for a supply chain with delivery time delays between every adjacent firms. Based on the supply chain model, we provide a new perspective of the bullwhip effect and show that the bullwhip effect is intrinsic in supply chains in the sense that the equilibrium state of each firm in the supply chain is a cumulative forward product of the ratios of order fulfillment and placement between adjacent firms toward the end customer demand. We also show that it is the multiple time delays instead of the constant end consumer demand that determine the stability of the equilibrium states. However, the consumer demand has impacts on the stability of the equilibrium states of the supply chain when the end retailer’s inventory decisions are linearly related to the end consumer demand.     

The effect of environmental parameters on product recovery

Economical and environmental issues are the main driving forces for the development of closed-loop supply chains. This paper examines the impact of environmental issues on long-term behaviour of a single product supply chain with product recovery. The environmental issues examined are the firm's `green image' effect on customer demand, the take back obligation imposed by legislation, and the state campaigns for proper disposal of used products. The behaviour of the system is analyzed through a dynamic simulation model based on the principles of the system dynamics (SD) methodology. This model includes all major inventories of new, used and recovered products and the flows among them. Inventory levels and flow rates are linked through differential equations. The dynamic model provides an experimental simulation tool, which can be used to evaluate the effect of environmental issues on long-term decision making in collection and remanufacturing activities and on product demand. Numerical analysis illustrates the potential uses of the methodology.