汽车行业供应链协同绩效评价及其应用

考虑汽车行业供应链协同绩效包含协同过程绩效、协同结果绩效和协同支持绩效,并结合客户服务和系统适应性,选择了30个汽车行业供应链协同评价指标,建立协同绩效评价指标体系.然后,选取以国内某汽车制造厂为核心企业的汽车行业供应链为例,运用模糊综合分析法对其供应链进行协同评价,实现了对该指标体系的量化,并对评价结果进行分析.结果表明,企业在过程、结果和支持等方面协同运作,可以提高供应链整体的协同绩效,从而进一步验证了评价指标体系的可行性和模糊综合评价方法的可操作性.     

Performance analysis and design of supply chains: a Petri net approach

In this paper, we investigated a dynamic modelling technique for analysing supply chain networks using generalised stochastic Petri nets (GSPNs). The customer order arrival process is assumed to be Poisson and the service processes at the various facilities of the supply chain are assumed to be exponential. Our model takes into account both the procurement process and delivery logistics that exist between any two members of the supply chain. We compare the performance of two production planning and control policies, the make-to-stock and the assemble-to-order systems in terms of total cost which is the sum of inventory carrying cost and cost incurred due to delayed deliveries. We formulate and solve the decoupling point location problem in supply chains as a total relevant cost (sum of inventory carrying cost and the delay costs) minimisation problem. We use the framework of integrated GSPN-queuing network modelling—with the GSPN at the higher level and a generalised queuing network at the lower level—to solve the decoupling point location problem.     

Supply chain performance evaluation using fuzzy network data envelopment analysis: a case study in automotive industry

Supply chain performance evaluation problems are evaluated using data envelopment analysis. This paper proposes a fuzzy network epsilon-based data envelopment analysis for supply chain performance evaluation. In the common data envelopment analysis models which are used for evaluation of decision-maker units efficiency, there are several inputs and outputs. One of the bugs of such models is that the intermediate products and linking activities are overlooked. Considering these intermediate activities and products, the current study evaluates the performance of decision-maker units in an automotive supply chain. There are ten decision-maker units in the supply chain in which there are three suppliers, two manufacturers, two distributors, and four customers. Moreover, the overall efficiency of input-oriented (input-based) model and input-oriented divisional efficiency are calculated. In order to improve the efficiencies, the projections onto the frontiers are obtained by using the outputs of the solved model and Lingo software. In order to show the applicability of the proposed model, it is applied on automotive industry, as a case study, to evaluate supply chain performance. Then, the overall efficiencies of DMUs and each sections (divisions) of DMUs were calculated separately. Therefore, every organization can apply this evaluation method for improving the performance of alternative factors.

     

The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.     

Achieving sharp deliveries in supply chains through variance pool allocation

Variability reduction and business process synchronization are acknowledged as key to achieving sharp and timely deliveries in supply chain networks. In this paper, we develop an approach that facilitates variability reduction and business process synchronization for supply chains in a cost effective way. The approach developed is founded on an analogy between mechanical design tolerancing and supply chain lead time compression. We first present a motivating example to describe this analogy. Next, we define, using process capability indices, a new index of delivery performance called delivery sharpness which, when used with the classical performance index delivery probability, measures the accuracy as well as the precision with which products are delivered to the customers. Following this, we solve the following specific problem: how do we compute the allowable variability in lead time for individual stages of the supply chain so that specified levels of delivery sharpness and delivery probability are achieved in a cost-effective way? We call this the variance pool allocation (VPA) problem. We suggest an efficient heuristic approach for solving the VPA problem and also show that a variety of important supply chain design problems can be posed as instances of the VPA problem. One such problem, which is addressed in this paper, is the supply chain partner selection problem. We formulate and solve the VPA problem for a plastics industry supply chain and demonstrate how the solution can be used to choose the best mix of supply chain partners.     

考虑供应链渠道冲突的零售商自有品牌产品定价方法

自有品牌产品定价是电子商务环境下零售商实施渠道管理的关键因素,其合理与否直接影响到零售商利润和供应链稳定.鉴于此,针对存在供应链渠道冲突的零售商自有品牌定价问题,从协调的角度,利用对偶理论与优化模型,构建了基于最小协调成本的零售商自有品牌产品定价决策方法,并利用其探讨协调的经济意义,求解零售商自有品牌产品最优定价.结果表明,所构建的模型能够有效描述和解决零售商自有品牌产品定价问题,并在一定程度上消除供应链渠道冲突,保证供应商和零售商长期有效合作和供应链可持续发展.     

A forward and reverse logistics shipment planning model

Many supply chains contain both forward and reverse logistics flows where forwarders are often asked to manage forward and reverse logistics activities in a cost-efficient manner. Reverse logistics jobs are different from forward logistics jobs, apart from the physical movement directions, and they have different logistics service requirements that usually require special facility setups. The choice of reverse logistics centres is also an important cost saving factor in a supply chain network. We consider cost saving activities through combining transportation activities and logistics activities in forward and reverse logistics jobs. A mixed 0–1 LP model is proposed to solve the shipment planning problem and the choice of reverse logistics centre. Managerial issues in implementation are discussed in an illustrative case.     

Demand uncertainty in construction supply chains: a discrete event simulation study

The delivery of construction projects is typically an assembly operation involving a high number of subassemblies and materials brought on site by the supply chain. However, although supply chain management in construction has attracted significant attention, paradoxically little focus has been placed on construction supply networks and operations. This paper places emphasis on supply chain operations by looking at the logistics function of construction material suppliers. Specifically, the paper examines the impact of demand uncertainty on supply chain performance in order to assess the capacity of material distribution companies to provide a timely and cost-efficient service to the construction industry. The study adopts a discrete event simulation approach to assess the impact of demand fluctuations on two crucial logistics performance measures; lead time and cost efficiency. The results show that lead times are particularly sensitive to fluctuations under conditions of low demand. The findings also reveal that, although transport is a significant cost element for lower demand levels, higher inventory costs result in a negative exponential relationship between increasing demand and cost efficiency.     

Schumann,a modeling framework for supply chain management under uncertainty

We present a modeling framework for the optimization of a manufacturing, assembly and distribution (MAD) supply chain planning problem under uncertainty in product demand and component supplying cost and delivery time, mainly. The automotive sector has been chosen as the pilot area for this type of multiperiod multiproduct multilevel problem, but the approach has a far more reaching application. A deterministic treatment of the problem provides unsatisfactory results. We use a 2-stage scenario analysis based on a partial recourse approach, where MAD supply chain policy can be implemented for a given set of initial time periods, such that the solution for the other periods does not need to be anticipated and, then, it depends on the scenario to occur. In any case, it takes into consideration all the given scenarios. Very useful schemes are used for modeling balance equations and multiperiod linking constraints. A dual approach splitting variable scheme is been used for dealing with the implementable time periods related variables, via a redundant circular linking representation.     

供应链纵向结构对EPR政策激励效果的影响研究

为了揭示供应链纵向结构对EPR政策激励效果的影响,本文通过构建EPR政策约束下由上游制造商和下游客户所组成的供应链决策模型,分别在纵向一体化和纵向分离两种典型的供应链纵向市场结构下,考察了EPR政策对制造商环保性能和可循环性设计决策的激励影响。结果表明:在不同的供应链纵向结构下,由于制造商与客户之间的利益协调机制存在着差异,使得EPR政策对制造商环境设计选择的激励效果将发生变化。在纵向一体化结构下EPR政策对制造商可循环性的激励效果更强;而EPR政策对环保性能的激励在哪种供应链纵向结构下更强是不确定的,最终还取决于行业本身在生产成本和环境成本等方面的特征。最后,基于本文的研究结论给出了EPR政策与产业政策相配套的政策建议。     

Logistics cost sharing in supply chains involving a third-party logistics provider

In many cases, end customers are sensitive to a product’s logistics service level which is provided by a third-party logistics (3PL) provider, therefore, the continuous improvement of the logistics service is imperative and valuable. However, the problem is that improving the logistics service benefits all of them, but is costly to only the 3PL provider. The 3PL provider is not willing to do this. Sharing the logistics cost is one solution to this problem. This study investigates cost sharing in two kinds of supply chains, i.e., one manufacturer-one 3PL provider-one retailer supply chain and two manufacturers-one 3PL provider-one retailer supply chain. Two types of cost sharing mechanisms, i.e., decentralized cost sharing mechanisms and centralized cost sharing mechanisms, are explored. Decentralized cost sharing mechanisms are proposed as contracts that chain members separately decide their cost sharing portions to optimize their own profits, ignoring the collective impacts of their decisions on the channel as a whole. Centralized cost sharing mechanisms are in the situation that chain members negotiate their cost sharing portions so that their profits are the shares of the entire supply chain’s profit, implying that the supply chain is coordinated perfectly. This study aims to analyse how cost sharing mechanisms affect supply chain performance and under what conditions chain members are willing to engage in cost sharing mechanisms. Conditions necessary for cost sharing mechanisms to achieve win-win outcomes are identified.     

低碳环境下供应链差异化定价与协调机制研究

以低碳和普通产品两个制造商和一个零售商组成的两级供应链系统为研究对象,探讨了供应链的差异化定价与协调机制问题。求解得到了两制造商和零售商的最优定价策略及可行的低碳产品生产成本范围。研究发现:1)分散决策的差异化定价策略无法达到供应链协调;2)在可行的低碳产品生产成本范围内,低碳产品制造商、零售商和整个供应链系统的利润都随低碳产品生产成本的增加而减少,只有普通产品制造商的利润随低碳产品生产成本的增加而增加。因此,降低低碳产品生产成本是促进低碳产品推广的关键。针对分散决策造成供应链效率损失的情况,采用Shapley值法进行协调,并给出了契约协调机制。最后,通过算例分析了消费者价格敏感性变化和低碳产品生产成本上升对最优决策和供应链利润的影响。     

Controlling the bullwhip effect in a supply chain system with constrained information flows

The bullwhip effect problem is one of the most important issues in supply chain management. Limited information sharing increases the difficulty of reducing the bullwhip effect and leads to inefficient supply chain management. The purpose of this paper is to explore new ways to reduce the bullwhip effect in supply chain systems that face uncertainties with respect to information sharing. We first present a supply chain state transition model, based on which we explore the endogenous mechanism of bullwhip effect, especially those related to impacts from limited information sharing. Then we propose a novel inventory control method and study the corresponding control optimization problem, with the aim of reducing inventory volatility in supply chains. Both quantitative analysis and simulation study are conducted. Simulation results show the effectiveness and flexibility of our proposed method in reducing bullwhip effect and in improving supply chain performance, even under conditions of limited information sharing.     

A continuous model for production–distribution system design

The production–distribution system design problem (PDSDP) involves decisions concerning the structure of a firm's supply chain. An overwhelming majority of the literature uses mixed integer programming formulations in representing such facility design decisions. In this paper, we present an alternative modeling framework, which is based on the use of continuous functions to represent spatial distributions of cost and customer demand. The proposed continuous model allows the derivation of a number of insights about the impact of problem parameters on facility design decisions. It is proposed that discrete and continuous modeling approaches complement each other.     

Time-dependent optimization of a multi-item uncertain supply chain network: A hybrid approximation algorithm

We consider the uncertain least cost shipping problem. The input is a multi-item supply chain network with time-evolving uncertain costs and capacities. Exploiting the operational law of uncertainty theory, a mathematical model of the problem is established and the indeterminacy factors are tackled. We use the scaling idea together with transformation approach and uncertainty programming to develop a hybrid algorithm to optimize and obtain the uncertainty distribution of the total shipping cost. We analyze the practical performance of the algorithm and present an illustrative example.     

An examination of the role of price insurance products in stimulating investment in agriculture supply chains for sustained productivity

This study examines how managing risk by introducing commodity price insurances may improve the likelihood of increased investment in agri-food supply chains. A model is introduced which shows how insurance products on index prices can reduce the uncertainty of the impact of investment, and also how lower investment can generate the same impact as a higher investment. To show our results, we use two different frameworks which include total profit (Pareto optimal) and Stackelberg game setups. The results demonstrate that in both frameworks the investment will have a greater impact when an insurance product is present. By implication, the study presents an encouraging message to the insurance industry to introduce products to secure supply chain actors’ revenue leading to an increase in investment rate. Consequently, the study offers insight into how the role of traditional government subsidies for protecting farmers, particularly the small to medium-sized farms, may be revisited by replacing some of the existing subsidisation policies with revenue insurance.     

Environmental supply chain network design using multi-objective fuzzy mathematical programming

The concern about environmental impact of business activities has spurred an interest in designing environmentally conscious supply chains. This paper proposes a multi-objective fuzzy mathematical programming model for designing an environmental supply chain under inherent uncertainty of input data in such problem. The proposed model is able to consider the minimization of multiple environmental impacts beside the traditional cost minimization objective to make a fair balance between them. A life cycle assessment-based (LCA-based) method is applied to assess and quantify the environmental impact of different options for supply chain network configuration. Also, to solve the proposed multi-objective fuzzy optimization model, an interactive fuzzy solution approach is developed. A real industrial case is used to demonstrate the significance and applicability of the developed fuzzy optimization model as well as the usefulness of the proposed solution approach.     

Shape Optimal Design Problem with Convective and Radiative Heat Transfer: Analysis and Implementation

We present a study of an optimal design problem for a coupled system, governed by a steady-state potential flow equation and a thermal equation taking into account radiative phenomena with multiple reflections. The state equation is a nonlinear integro-differential system. We seek to minimize a cost function, depending on the temperature, with respect to the domain of the equations. First, we consider an optimal design problem in an abstract framework and, with the help of the classical adjoint state method, give an expression of the cost function differential. Then, we apply this result in the two-dimensional case to the nonlinear integro-differential system considered. We prove the differentiability of the cost function, introduce the adjoint state equation, and give an expression of its exact differential. Then, we discretize the equations by a finite-element method and use a gradient-type algorithm to decrease the cost function. We present numerical results as applied to the automotive industry.     

基于RS和SVM的动态供应链成员选择算法

良好的成员选择方法是动态供应链平稳运行的重要基础,针对动态供应链成员选择时面临决策属性多且可供决策分析数据样本少的难题,提出了基于粗糙集和支持向量机的动态供应链成员选择算法,核心是应用粗糙集进行属性约简,然后结合支持向量机进行链上成员分类.方法在保证不会降低分类性能的前提下,达到降低数据维数和分类过程中复杂度的目的.     

Demand forecast sharing in a dual-channel supply chain

We assess the benefits of sharing demand forecast information in a manufacturer–retailer supply chain, consisting of a traditional retail channel and a direct channel. The demand is a linear function of price with a Gaussian primary demand (i.e., zero-price market potential). Both the manufacturer and the retailer set their price based on their forecast of the primary demand. In this setting, we investigate the value of sharing demand forecasts. We analyze the ‘make-to-order’ scenario, in which prices are set before and production takes place after the primary demand is known, and the ‘make-to-stock’ scenario, in which production takes place and prices are set before the primary demand is known. We also compare the supply chain performance with and without the direct channel under some assumptions (production cost is zero, and each demand function has the same slope of price). We find that the direct channel has a negative impact on the retailer’s performance, and, under some conditions, the manufacturer and the whole supply chain are better off. Our research extends and complements prior research that has investigated only the inventory and replenishment-related benefits of information sharing.