A hybrid approach to select the best sourcing policy using stochastic programming

Supply contracts are known as the communication link among supply chain members. As sourcing of required goods is a challenging issue for supply chain members, different sourcing types for different market conditions have been presented in the literature. However, the uncertain price condition has not been much focused in the previous studies, and in the limited works on this issue the correlation between the periods has been ignored. In this paper, sourcing policies are analyzed in a multi-period system in which price and demand follow a Geometric Brownian Motion with drift. Wholesale contract, option contract, and purchase from the spot market are considered as the sourcing alternatives for the buyer. This paper applies the stochastic programming approach to model these three types of sourcing based upon price and demand uncertainties. Afterwards, a hybrid supply model of these sourcing types is developed. By a numerical example, the simulation results of the developed models reveal that each individual sourcing alternative can be selected as the best one in each price and demand behavior. The results also suggest that the proposed hybrid model dominates each of the individual sourcing types. Finally, the paper reports the effects of cost parameter alterations on the solution of the hybrid model through sensitivity analysis.     

期权工具存在下的最优混合采购策略研究

原材料价格与需求不确定下,研究制造商混合期权合约、长期合约、现货采购的最优采购策略。利用期望效用模型建立了一个风险规避制造商的决策模型,并得到效用函数为二次效用函数下制造商的最优采购策略。研究结果表明,制造商最优采购量与风险规避度的关系取决于原材料期望价格与长期合约价格以及期权价格间的相对大小关系;当价格漂移率增加时,长期合约预定数量增加,期权购买量减小;当价格波动率或长期合约价格增加时,长期合约预定数量减少,期权购买量增加;采用混合采购策略可提高制造商的期望效用水平。     

Supply chain coordination based on return contracts with a threshold ordering quantity

Return contracts are commonly used by companies selling products with short life cycles and highly uncertain demand. Current research on return contracts assumes suppliers are responsible for all surplus products. In practice, retailers tend to order more than necessary and leave suppliers with large after‐season returns. To mitigate the problem, a new type of return contract with a threshold ordering quantity has been developed by some enterprises. Under these contracts, suppliers specify a threshold for retailers’ ordering quantity. They buy back only the portion in excess of the threshold. In this paper, we show that this new type of contract can achieve two objectives: (a) the supply chain is coordinated, and (b) both the supplier and the retailer can gain more profit than they can gain under a wholesale‐price‐only contract. The new contract does not require any manipulation of wholesale prices. This makes it more acceptable in practice by supply chain members. We also illustrate our findings in a numerical example.     

Capacity reservation under supply uncertainty

Shortages of input materials and components used in the production process often adversely influence sales of manufacturing firms. Manufacturers can guarantee delivery of the inputs by initiating capacity reservation arrangements with their suppliers. We study a multi-period capacity reservation contract between a manufacturer and a long-term supplier when there is uncertainty about the quantity of an input item available in the spot market. The contract requires the manufacturer to pay a fixed amount to the supplier at each period. In return, the supplier guarantees availability of the input up to a predetermined level of volume. The manufacturer can also meet some of input needs from a spot market, which may exist in the form of a B2B electronic exchange. Optimal inventory policy for the manufacturer in this dual supplier environment is derived analytically. Numerical examples are used to explore the strategies of the manufacturer and the supplier in certain and uncertain supply environments. We find that uncertain input markets lead to an increase in the share of inputs purchased in advance via long-term contracts. Capacity reservation contracts are shown to increase capacity utilization of the supplier compared to the traditional unit-price based supply contracts.     

基于期权与现货市场的供应链契约式协调的研究

通过期权机制，建立了电子市场与传统契约市场共存下的供应链中各决策主体的决策模型，求得协调状况下供应商的最优价格政策、产能决策和零售商的最优购买决策，数值实例对各决策模型中的影响因素进行了敏感性分析，进一步验证了结论的有效性．     

An integration methodology based on fuzzy inference systems and neural approaches for multi-stage supply-chains

This paper proposes a methodology for supply chain (SC) integration from customers to suppliers through warehouses, retailers, and plants via both adaptive network based fuzzy inference system and artificial neural networks approaches. The methodology presented provides this integration by finding the requested supplier capacities using the demand and order lead time information across the whole SC in an uncertain environment. The SC structure is investigated stage by stage. The sensitivity analysis is made by comparing the obtained results with the traditional statistical techniques. A company serving in durable consumer goods industry that produces consumer electronics in Istanbul, Turkey was examined to demonstrate the applicability of the proposed methodology.     

Modeling and optimization of two-stage procurement in dual-channel supply chain

An online marketing platform should be designed to fairly take the benefits of buyers and suppliers into consideration based on their risk preferences and business strategies. In this paper, the dual-channel supply chain models are developed to implement the risk-averse strategy for buyers and risk-neutral strategy for suppliers, respectively. The buyers under the consideration are the manufacturers who acquire raw materials, parts, or components to make their final products. The major factors in the developed models include the risk preferences of buyers and suppliers, random price fluctuations of goods, and varying demands of final products. To reflect the purchasing practice of a manufacturer, (1) a supply chain is considered to have two supply channels, i.e., contract-based purchase with a lead-time before the goods are used and a direct purchase from online spot markets when the goods are used; (2) the time factor on decision making is specially taken into account, and the procurements are divided into the contract stage of purchase and online stage of purchase. Gaming analysis is conducted to develop the supply chain models for manufactures and suppliers to implement their purchasing or pricing strategies. The simulation is conducted and the result has shown that two-stage purchases in a dual-channel supply chain have improved the performances of suppliers and manufacturers in terms of the profits they can make, their supply–demand relations, and their adjustability to uncertainties in globalized and segmented markets. The proposed model has its significance for manufacturers to better control the price risk of goods and the demand risk of final products; on the other hand, suppliers can benefit from adjusting dynamic sales using online spot markets.     

基于成本共担契约的生鲜供应链保鲜努力机制

研究由一个供应商与一个零售商组成的生鲜供应链,在分散式决策与集中式决策下的最优保鲜努力水平.考虑两类成本共担契约方式:一类为零售商单独提供成本共担契约的方式,另一类为供应商与零售商二者博弈制定成本共担契约的方式;同时,比较两类成本共担契约对供应链整体保鲜努力水平的影响.结果表明,成本共担契约对生鲜供应链整体生鲜水平的提高非常有益,且有利于提高供应商、零售商及供应链整体的利润,其中供应商与零售商二者博弈制定成本共担契约的方式最为有效.另外,保鲜成本与消费者生鲜敏感程度分别对供应链的发展起着消极和积极的作用.     

B2B电子市场下供应链期权合同协调模型与优化

研究B2B电子市场下双源渠道的供应链期权合同协调模型与优化问题.在需求不确定条件下,推导了传统供应链中分销商的最优批量定货量和最优期权购买量,以及供应商的最优生产量.建立了B2B电子市场下的供应链期权合同模型,结合长期合约的稳定性和现货采购的灵活性,讨论了分销商和供应商的最优决策.最后从渠道协调的角度,讨论了传统供应链和B2B电子市场下的期权合同能有效协调供应链的充分条件.     

On coordination under random yield and random demand

This paper analyzes coordination in a supply chain with random yield and random demand (SCRYRD). We study wholesale price, buy-back, revenue share, quantity discount and quantity flexibility contracts. We show that the randomness in the yield does not change the coordination ability of the contracts but affects the values of the contract parameters. In particular, all contracts are shown to coordinate the supply chain under voluntary compliance except the wholesale price contract. We also provide a sensitivity analysis of the optimal policy parameters to the cost and demand parameters.     

A solution procedure for mixed-integer nonlinear programming formulation of supply chain planning with quantity discounts under demand uncertainty

Quantity discount policy is decision-making for trade-off prices between suppliers and manufacturers while production is changeable due to demand fluctuations in a real market. In this paper, quantity discount models which consider selection of contract suppliers, production quantity and inventory simultaneously are addressed. The supply chain planning problem with quantity discounts under demand uncertainty is formulated as a mixed-integer nonlinear programming problem (MINLP) with integral terms. We apply an outer-approximation method to solve MINLP problems. In order to improve the efficiency of the proposed method, the problem is reformulated as a stochastic model replacing the integral terms by using a normalisation technique. We present numerical examples to demonstrate the efficiency of the proposed method.     

A holonic approach based integration methodology for transportation and warehousing functions of the supply network

The supply chain (SC) is often defined as a network that is composed of different functions, including suppliers, manufacturing plants, warehouses/distribution centers, retailers and customers. A supply network (SN) is a sequence of different and multiple numbers of functions and individual functional units that must satisfy all capacities and demand requirements imposed by customers with minimum cost to the network. The most important functions of a SN are warehousing and transportation functions. This paper addresses the warehousing and transportation network design problem that involves determining the best strategy for distributing the sub-products from the suppliers to the warehouse and from the warehouse to the manufacturers. Considering some similarities between holonic systems and SN systems, a holonic approach based modeling methodology is proposed in this study. A multiple supplier, single warehouse and multiple manufacturer system are considered to be an integrated warehousing and transportation network. Consequently, a linear programming model is presented to maximize the profit of both of the overall SN and the individual functional units of the SN functions.     

The effect of intention analysis-based fraud detection systems in repeated supply Chain quality inspection: A context of learning and contract

As a result of the information asymmetry on product quality, there is a risk of unethical suppliers defrauding buyers in a supply chain. Buyers often conduct quality inspection on shipments and frame supply contracts to punish quality fraud. Due to cost concerns, buyers need to estimate the suppliers’ fraud possibilities and choose appropriate testing methods and frequencies. As suppliers’ fraud intentions depend on their cost-benefit analysis, it is possible to analyze suppliers’ fraud intention with appropriate modeling of their profit-seeking behavior. In this research, we are interested in how fraud intention analysis may affect the quality inspection process. It should be noted that quality inspection can be a repeated process, with suppliers and buyers conducting multiple rounds of transactions (including transactions with frauds) and learning about each other during the process. Their supply contracts may also affect suppliers’ profit-seeking attitude. We conduct a laboratory experiment to examine the effect of fraud intention analysis systems on inspection decision making considering the learning and contract effects. We put the experiment in the context of a dairy supply chain as a critical and interesting example application. The experiment shows that if there are no strong punitive terms for fraud in the contract, fraud intention analysis can improve buyers’ decision-making efficiency after controlling the learning effect, in terms of decision time, inspection cost, and correctness of rejecting suppliers’ fraudulent shipments.     

A framework for evaluation of coordination by contracts: A case of two-level supply chains

A supply chain consists of disparate but inter-dependent members who are dependent on each other to manage various resources (such as inventory, money and information). The conflicting objectives and lack of coordination between these members may often cause uncertainties in supply and demand. Coordination may help in managing inter-dependencies and reducing uncertainties. Typically, a mechanism is required to streamline the whole supply chain and motivate all the members to be a part of the entire supply chain for sharing risks and rewards through supply chain contracts.The objective of this paper is to explore the applicability and benefits of the contracts. A two-phase framework is proposed consisting of a decision support tool and a graph-theoretic model for evaluation of coordination in a two-level supply chain. In Phase I, an analytical model is proposed based on the classical newsboy problem. Various contract mechanisms have been explored through a decision support tool based on the simulation. The effectiveness of these contracts is evaluated through a graph-theoretic model in Phase II. It is expected that by designing the contracts as per the requirements of the supply chain members as well as the whole supply chain, supply chain performance may be improved.     

B2B在线市场运作、协调与优化问题研究进展

分析了在线市场的传媒背景、信息透明度和传媒多样性问题，并分析了在线市场的协调策略和供应链合同策略问题．作为B2B在线市场的主流模式，重点分析了以采购商为中心的B2B在线市场，特别是其中的供应链协调，如回购退货协调、远期和现货合同协调问题．进一步分析了以供应商和第三方为中心的B2B在线市场的运作、协调与优化问题．最后，提出了B2B在线市场运作比例和规模、双边际化和牛鞭效应、供应链合同、资金财务策略和信息共享环境下的协调等若干需深入探讨的问题．     

基于随机需求与产能限制的供应链协同优化研究

供应链所面临的需求随机性以及供应方的产能限制对供应链协同路径优化有着显著影响。已有研究并未考虑二者综合作用下供应链各参与主体的行为选择机理及协同优化的实现路径。对此,建立了一个包含多制造商与单一销售商的二级供应链模型,运用非合作博弈的方法求得稳定均衡解,并探讨了实现供应链协同优化的有效路径,从而有助于为供应链参与主体提供决策支持。     

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。     

Evaluation of sourcing contracts in wood supply procurement using simulation

Procurement operations in forest companies are exposed to various risks, which may increase procurement costs. Examples of risks are the contract's unreliability and contract breach. Deterministic planning models cannot perfectly reflect the complexities of real-world applications in the presence of sourcing risks when the future is uncertain. In practice, forest industries use contracts to guarantee the wood supply. Monthly forecasts are prepared for the delivery volume and are primarily based on the experience of procurement staff and the total volume of contracts. Missed deliveries in the contracts lead to a mismatch between the supply and demand for wood fiber and increase the costs of procurement as a result of high inventory costs or expensive purchases from the open market. Previous studies on simulating the impact of sourcing risks on procurement operations have been conducted; however, none have addressed the selection of procurement contracts in the presence of sourcing risks. In forest industry, numerous suppliers are available with sourcing contracts. Each contract possesses its own characteristics such as flexibility, volume, schedule, and price of delivery. A Monte Carlo simulation approach is implemented to analyze the behavior of a deterministic planning approach. Random events are generated by formulating different types of sourcing risks, having either short- or long-term impact. The simulation is embedded with a deterministic planning model in each period. Results showed that management of sourcing risks is easier with flexible contracts than with fixed contracts, despite their higher purchasing cost.     

A supply chain contract with flexibility as a risk-sharing mechanism for demand forecasting

Demand forecasting is one of the main causes of the bullwhip effect in a supply chain. As a countermeasure for demand uncertainty as well as a risk-sharing mechanism for demand forecasting in a supply chain, this article studies a bilateral contract with order quantity flexibility. Under the contract, the buyer places orders in advance for the predetermined horizons and makes minimum purchase commitments. The supplier, in return, provides the buyer with the flexibility to adjust the order quantities later, according to the most updated demand information. To conduct comparative simulations, four-echelon supply chain models, that employ the contracts and different forecasting techniques under dynamic market demands, are developed. The simulation outcomes show that demand fluctuation can be effectively absorbed by the contract scheme, which enables better inventory management and customer service. Furthermore, it has been verified that the contract scheme under study plays a role as an effective coordination mechanism in a decentralised supply chain.     

Integrated Inventory Control and Facility Location Decisions in a Multi-Echelon Supply Chain Network with Hubs

This paper develops mathematical models to coordinate facility location and inventory control for a four-echelon supply chain network consisting of multiple suppliers, warehouses, hubs and retailers. The hubs help in reducing transportation costs by consolidating products from multiple warehouses and directing the larger shipments to the retailer. The integrated models studied in this paper simultaneously determines three types of decisions: (i) facility location—the number and location of warehouses and hubs, (ii) allocation—assignment of suppliers to located warehouses and retailers to located warehouses via the location hubs, and (iii) inventory control decisions at each located warehouse. The goal is to minimize the facility location, transportation and the inventory costs. A mixed integer nonlinear programming formulation is first presented. The nonlinear integer programming formulation is then transformed into a conic mixed integer program and a novel and compact conic mixed integer programming formulation. Computational runs are conducted using commercial solvers to compare the performance of the different formulations. The compact conic mixed integer programming formulation was found to significantly outperform the other formulations by achieving significant computational savings. The results demonstrate that large scale instances of certain multi-echelon supply chain network design problems can be solved using commercial solvers through intelligent reformulation of the model.