外包制造下政府补贴对低碳供应链影响分析

为分析外包制造下,政府补贴对低碳供应链竞争的影响,基于低碳产品外包制造,构建一个制造商、一个外包制造商和一个销售商组成的博弈模型。基于此模型,对比分析政府三种补贴策略对两种产品市场竞争机理的影响。研究得到:政府补贴给制造商或销售商时,单位委托制造价格要高于补贴给外包制造商时,也即,当政府采取补贴策略且不补贴给外包制造商时,外包制造商会通过增加单位委托制造价格转移政府补贴;政府补贴策略对单位普通产品批发价格和零售价格无影响,但政府补贴策略会减少普通产品销售量,增加低碳产品销售量;政府补贴虽然减少普通产品收益,但政府补贴增加低碳产品收益,且低碳产品增加收益大于普通产品减少收益,也即政府补贴增加制造商和销售商的利润;政府补贴策略减少两种产品对环境造成的影响,增加消费者剩余和社会剩余。     

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.     

Supply chain scheduling in a collaborative manufacturing mode: model construction and algorithm design

In collaborative manufacturing, the supply chain scheduling problem becomes more complex according to both multiple product demands and multiple production modes. Aiming to obtain a reasonable solution to this complexity, we analyze the characteristics of collaborative manufacturing and design some elements, including production parameters, order parameters, and network parameters. We propose four general types of collaborative manufacturing networks and then construct a supply chain scheduling model composed of the processing costs, inventory costs, and two penalty costs of the early completion costs and tardiness costs. In our model, by considering the urgency of different orders, we design a delivery time window based on the least production time and slack time. Additionally, due to the merit of continuously processing orders belonging to the same product type, we design a production cost function by using a piecewise function. To solve our model efficiently, we present a hybrid ant colony optimization (HACO) algorithm. More specifically, the Monte Carlo algorithm is incorporated into our HACO algorithm to improve the solution quality. We also design a moving window award mechanism and dynamic pheromone update strategy to improve the search efficiency and solution performance. Computational tests are conducted to evaluate the performance of the proposed method.

     

Design outsourcing in the fashion supply chain: OEM <Emphasis Type="Italic">versus</Emphasis> ODM

Design innovation is the engine of fashion. Many fashion firms outsource design innovation to their suppliers. Design outsourcing is on the rise in the fashion supply chain, but research in this area lags behind industry practice. In this paper, we examine how design outsourcing affects the supply chain, and we compare supply chain performance under an Original Equipment Manufacturer (OEM) strategy versus an Original Design Manufacturer (ODM) strategy. We evaluate a market size outsourcing model where design enhancement influences market size, and a success probability outsourcing model where design enhancement influences the success probability of innovation. We find that when the supplier trades with the retailer via a wholesale price contract under the ODM strategy, the supplier has no incentive to invest in innovation. In the market size outsourcing model, the design innovation in the centralized supply chain is higher than that under the OEM strategy. However, in the success probability outsourcing model, the success probability of innovation under the OEM strategy is higher than that in the centralized supply chain. Furthermore, we find that a profit sharing contract can achieve supply chain coordination under both OEM and ODM strategies; whereas, revenue sharing and buyback contracts cannot.     

Integrated location and two-echelon inventory network design under uncertainty

In this paper, we propose a two-stage stochastic model to address the design of an integrated location and two-echelon inventory network under uncertainty. The central issue in this problem is to design and operate an effective and efficient multi-echelon supply chain distribution network and to minimize the expected system-wide cost of warehouse location, the allocation of warehouses to retailers, transportation, and two-echelon inventory over an infinite planning horizon. We structure this problem as a two-stage nonlinear discrete optimization problem. The first stage decides the warehouses to open and the second decides the warehouse-retailer assignments and two-echelon inventory replenishment strategies. Our modeling strategy incorporates various probable scenarios in the integrated multi-echelon supply chain distribution network design to identify solutions that minimize the first stage costs plus the expected second stage costs. The two-echelon inventory cost considerations result in a nonlinear objective which we linearize with an exponential number of variables. We solve the problem using column generation. Our computational study indicates that our approach can solve practical problems of moderate-size with up to twenty warehouse candidate locations, eighty retailers, and ten scenarios efficiently.     

Supply chain network capacity competition with outsourcing: a variational equilibrium framework

This paper develops a supply chain network game theory framework with multiple manufacturers/producers, with multiple manufacturing plants, who own distribution centers and distribute their products, which are distinguished by brands, to demand markets, while maximizing profits and competing noncooperatively. The manufacturers also may avail themselves of external distribution centers for storing their products and freight service provision. The manufacturers have capacities associated with their supply chain network links and the external distribution centers also have capacitated storage and distribution capacities for their links, which are shared among the manufacturers and competed for. We utilize a special case of the Generalized Nash Equilibrium problem, known as a variational equilibrium, in order to formulate and solve the problem. A case study on apple farmers in Massachusetts is provided with various scenarios, including a supply chain disruption, to illustrate the modeling and methodological framework as well as the potential benefits of outsourcing in this sector.     

A dynamic inventory model with supplier selection in a serial supply chain structure

Considering the inherent connection between supplier selection and inventory management in supply chain networks, this article presents a multi-period inventory lot-sizing model for a single product in a serial supply chain, where raw materials are purchased from multiple suppliers at the first stage and external demand occurs at the last stage. The demand is known and may change from period to period. The stages of this production–distribution serial structure correspond to inventory locations. The first two stages stand for storage areas for raw materials and finished products in a manufacturing facility, and the remaining stages symbolize distribution centers or warehouses that take the product closer to customers. The problem is modeled as a time-expanded transshipment network, which is defined by the nodes and arcs that can be reached by feasible material flows. A mixed integer nonlinear programming model is developed to determine an optimal inventory policy that coordinates the transfer of materials between consecutive stages of the supply chain from period to period while properly placing purchasing orders to selected suppliers and satisfying customer demand on time. The proposed model minimizes the total variable cost, including purchasing, production, inventory, and transportation costs. The model can be linearized for certain types of cost structures. In addition, two continuous and concave approximations of the transportation cost function are provided to simplify the model and reduce its computational time.     

An operational profit sharing and transfer pricing model for network-manufacturing companies

New age companies are forging partnerships with other firms to market products that have been assembled through manufacturing activities distributed at different locations. These locations belong to more than one company and the product passes through these different sites during its manufacturing stages. This manufacturing collaboration is known as network-manufacturing. According to the network philosophy, companies form alliances to manufacture a product and share in its operating profits. This paper proposes a framework and methodology for profit sharing and transfer-pricing between network companies. We propose a paradigm that enables maximization of operating profits by the manufacturing-network in its larger supply chain, suggesting a departure from the model that maximizes profits for the individual company within the sphere of its own supply chain.     

规模效应下产品具有可替代性的竞争企业的外包决策

针对产品具有一定替代性的两个竞争企业(分别为企业1和企业2)和存在规模效应的上游供应商的外包决策问题, 构建了企业1 外包前后各方的利润模型,求解了下游企业的外包和自产的最优策略以及供应商的最佳批发价格,分析了企业1 的外包策略对企业2 和供应商的外包决策的影响,比较了产品替代性对外包前后各决策变量的影响。研究发现:当企业的单位生产成本高于外包成本时,企业也可能选择自产;而当企业的单位生产成本低于外包成本时,企业也可能选择产品外包。并对模型进行进一步的拓展,比较了下游企业作顺序和同时外包决策两种情景的异同。     

Formation of a strategic manufacturing and distribution network with transfer prices

We propose a profit maximization model for the decision support system of a firm that wishes to establish or rationalize a multinational manufacturing and distribution network to produce and deliver finished goods from sources to consumers. The model simultaneously evaluates all traditional location factors in a manufacturing and distribution network design problem and sets intra-firm transfer prices that take account of tax and exchange rate differentials between countries. Utilizing the generalized Benders decomposition approach, we exploit the partition between the product flow and the cash allocation (i.e., the pricing and revenue assignment) decisions in the supply chain to find near optimal model solutions. Our proposed profit maximizing strategic planning model produces intuitive results. We offer computational experiments to illustrate the potential valuable guidance the model can provide to a firm's supply chain design strategic planning process.     

Designing optimal global supply chains at Dow AgroSciences

The design of the underlying supply chain network can have a tremendous impact on the profitability, manageability, and level of risk of a global supply chain. Taxes, duties, and tariffs vary from country to country as well as trading bloc to trading bloc and can consume as much as 10% of the revenues of certain products. In the highly regulated business environment of agricultural chemicals, the country of origin of an active ingredient can determine where the final product can be marketed and the amount of taxes and duties applied to the product, making it necessary to trace all batches of product through many layers of the supply chain to their sources. This article presents a mixed integer linear programming model in use at Dow AgroSciences LLC that simultaneously optimizes the network design underlying global supply chains and the monthly production and shipping schedules for maximum profitability. This work contributes to the supply chain design literature by demonstrating a novel method of tracing products to their source for inventory valuation, taxation, and duty computation in a production environment where the products change into other products as they pass through nodes in the network. It also demonstrates an iterative scheme for determining unit fixed costs for fixed cost allocation for the same purposes. Finally, it provides a case study of a supply chain design initiative in a global enterprise.     

Planning and coordination of production and distribution facilities for multiple commodities

We study an integrated logistics model for locating production and distribution facilities in a multi-echelon environment. Designing such logistics systems requires two essential decisions, one strategic (e.g., where to locate plants and warehouses) and the other operational (distribution strategy from plants to customer outlets through warehouses). The distribution strategy is influenced by the product mix at each plant, the shipments of raw material from vendors to manufacturing plants and the distribution of finished products from the plants to the different customer zones through a set of warehouses. First we provide a mixed integer programming formulation to the integrated model. Then, we present an efficient heuristic solution procedure that utilizes the solution generated from a Lagrangian relaxation of the problem. We use this heuristic procedure to evaluate the performance of the model with respect to solution quality and algorithm performance. Results of extensive tests on the solution procedure indicate that the solution method is both efficient and effective. Finally a `real-world' example is solved to explore the implications of the model.     

Make-or-buy service capacity decision in a supply chain providing after-sales service

We consider a supply chain comprising a manufacturer and a retailer. The manufacturer supplies a product to the retailer, while the retailer sells the product bundled with after-sales service to consumers in a fully competitive market. The sales volume is affected by the retailer’s service-level commitment. The retailer can build service capacity in-house at a deterministic price before service demand is realized, or buy the service from an outsourcing market at an uncertain price after service demand realization. We find that the outsourcing market encourages the retailer to make a higher level of service commitment, while prompting the manufacturer to reduce the wholesale price, resulting in more demand realization. We analyze how the expected cost of the service in the outsourcing market and the retailer’s risk attitude affect the decisions of both parties. We derive the conditions under which the retailer is willing to build service capacity in-house and under which it will buy the service from the outsourcing market. Moreover, we find that the manufacturer’s sharing with the retailer the cost to build service capacity improves the profits of both parties.     

Supply chain networks,wages, and labor productivity: insights from Lagrange. analysis and computations

The COVID-19 pandemic has dramatically demonstrated the importance of labor to supply chain network activities from production to distribution with shortfalls in labor availability, for numerous reasons, resulting in product shortages and the reduction of profits of firms. Even as progress has been made through vaccinations, issues associated with labor are still arising. Increasing wages is a strategy to enhance labor productivity and, also to ameliorate, in part, labor shortages, but has not, until this work, been explored in a full supply chain network context. Specifically, in this paper, a game theory supply chain network model is constructed of firms competing in producing a substitutable, but differentiated, product, and seeking to determine their equilibrium product path flows, as well as hourly wages to pay their workers, under fixed labor amounts associated with links, and wage-responsive productivity factors. The theoretical and computational approach utilizes the theory of variational inequalities. We first introduce a model without wage bounds on links and then extend it to include wage bounds. Lagrange analysis is conducted for the latter model, which yields interesting insights, as well as an alternative variational inequality formulation. A series of numerical examples reveals that firms can gain in terms of profits by being willing to pay higher wages, resulting in benefits also for their workers, as well as consumers, who enjoy lower demand market prices for the products. However, sensitivity analysis should be conducted to determine the range of such wage bounds. Ultimately, we observed, that the profits may decrease and then stabilize. This work adds to the literature on the integration of concepts from economics and operations research for supply chain networks and also has policy implications.

     

Supply planning models for a remanufacturer under just-in-time manufacturing environment with reverse logistics

We study a supply planning problem in a manufacturing system with two stages. The first stage is a remanufacturer that supplies two closely-related components to the second (manufacturing) stage, which uses each component as the basis for its respective product. The used products are recovered from the market by a third-party logistic provider through an established reverse logistics network. The remanufacturer may satisfy the manufacturer’s demand either by purchasing new components or by remanufacturing components recovered from the returned used products. The remanufacturer’s costs arise from product recovery, remanufacturing components, purchasing original components, holding inventories of recovered products and remanufactured components, production setups (at the first stage and at each component changeover), disposal of recovered products that are not remanufactured, and coordinating the supply modes. The objective is to develop optimal production plans for different production strategies. These strategies are differentiated by whether inventories of recovered products or remanufactured components are carried, and by whether the order in which retailers are served during the planning horizon may be resequenced. We devise production policies that minimize the total cost at the remanufacturer by specifying the quantity of components to be remanufactured, the quantity of new components to be purchased from suppliers, and the quantity of recovered used products that must be disposed. The effects of production capacity are also explored. A comprehensive computational study provides insights into this closed-loop supply chain for those strategies that are shown to be NP-hard.     

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.     

Supply chain dynamic configuration as a result of new product development

This study considers supply chain network configuration in an innovative environment while the new product development (NPD) will affect the supply chain configuration (SCC). The time of new product introduction has a significant effect on the market performance while it has an effect on the supply chain configuration. Supplier integration into the new product introduction is the key parameter for successfully new product introduction, which may contribute to supply chain reconfiguration. Consequently By considering the new product development concept, we may face with dynamic supply chain configuration during a planning horizontal time. In this study, a new model is presented to consider the dynamic configuration of a supply chain by developing new products. In the proposed model, the dynamic configuration of a supply chain and the new product launching time is optimized simultaneously. The proposed model considers production, sales and transportation planning for the entire supply chain in order to achieve an integrative and efficient supply as well. Then some numerical analyses have been done to show the applicability of the proposed model. The results show that the new product development has a significant effect on the configuration of supply chain.     

The effect of product variety on supply-chain performance

We present a stylized model for analyzing the effect of product variety on supply-chain performance for a supply chain with a single manufacturer and multiple retailers. The manufacturer produces multiple products on a shared resource with limited capacity and the effect of changeovers on supply-chain cost is due primarily to setup time rather than setup cost. We show that the expected replenishment lead time and the retailers' costs are concave increasing in product variety and that the increase is asymptotically linear. Thus, if setup times are significant, the effect of product variety on cost is substantially greater than that suggested by the risk-pooling literature for perfectly flexible manufacturing processes, where the cost increases proportionally to the square root of product variety. We demonstrate that disregarding the effect of product variety on lead time can lead to poor decisions and can lead companies to offer product variety that is greater than optimal. The results of our analysis enable decision-makers to quantify the effect of product variety on supply-chain performance and thus to determine the optimal product variety to offer. The results can also be used to evaluate how changes in the manufacturing process, the supply-chain structure, and the customer demand rate can improve the performance of supply chains with high product variety.     

Strategic interactions in service supply chain with horizontal competition

We analyze strategic interaction issues that arise in service supply chain, such as consulting, service outsourcing, and travel service. To capture strategic interactions in service supply chain, we study a case where there are two service vendors providing competing service products and selling them through a common Service Integrator. In particular, we derive and compare equilibrium solutions (e.g. service prices, wholesale prices, service volumes) for the service supply chain under three different scenarios. We then study the effect of key parameters in the model upon the equilibrium solution using sensitivity analysis, and discuss our results along with a numerical experiment. Finally, future research direction is pointed out.     

由零售商负责回收的多期闭环供应链网络均衡

本文研究了零售商回收模式下多期闭环供应链网络均衡问题。制造商通过零售渠道将产品销售给消费者,以满足消费市场需求,同时消费产生的废旧品由零售商回收返回制造商处进行再制造,通过产品库存和回收废旧品连接相邻规划期。运用变分不等式理论和互补理论,分别刻画了制造市场、零售市场和消费市场的均衡,接着构建了多期闭环供应链网络均衡模型。利用变分不等式的投影收缩算法,对模型进行求解。算例着重分析了废旧品利用率对网络均衡状态和供应链成员利润的影响。结果表明:当制造商的废旧品利用率逐渐增加时,回收量逐渐增加,制造商的利润先减后增,零售商利润一直增加,而供应链总利润一直增加,供应链网络中的最优决策变量主要受到回收量约束的影响。