A stochastic production planning model under uncertain seasonal demand and market growth

This paper proposes a stochastic production planning model for an international enclosure manufacturing company with seasonal demand and market growth uncertainty. The company purchases material and subassembly from overseas and long lead times have been observed. To prevent excess inventory and stockout, the company is required to forecast its demand and project its purchasing decisions and production load to its key suppliers in an effort to reduce risks for both parties. To assist purchasing and production decisions, a two-stage stochastic production planning model that explicitly includes uncertainty is developed with the goal of minimising the total production, inventory, and overtime costs under all scenarios. The model is solved using real data from the company and results have demonstrated the effectiveness of the model compared with various deterministic models. Parametric analyses are performed to derive managerial insights related to issues such as overtime usage, inventory holding costs and the proper selection of scenarios under pessimist, neutral, and optimist outlooks. The model has been implemented and an annual saving of more than $400,000 in inventory cost has been achieved.     

Manufacturing lot-sizing,procurement and delivery schedules over a finite planning horizon

In this study, an integrated manufacturing system for technology-related companies whose products are experiencing continuous price decrease during the life cycle is studied for optimal procurement, production and delivery schedules over a finite planning horizon. The model considers the inventory cost both at manufacturing and at delivery from supplier. Since the price is continuously decreasing, a manufacturing firm delivers the finished goods in small quantities frequently. Frequent deliveries in small lots are effective to reduce the total cost of the supply chain. The key for high-tech industries is to reduce the inventory holding time since the component prices are continuously decreasing, and this can only be achieved by implementing an efficient supply chain. Therefore, the main purpose of this paper is to develop an integrated inventory model for high-tech industries in JIT environment under continuous price decrease over finite planning horizon while effectively and successfully accomplishing supply chain integration so that the total cost of the system is minimal. An efficient algorithm is developed to determine the optimal or near-optimal lot sizes for raw material procurement, and manufacturing batch under a finite planning horizon. Finally, the solution technique developed for the model is illustrated with numerical examples.     

Flexible work-in-process production system in supply chain management under quality improvement

For a complex product production, any flexible manufacturing system with a work-in-process inventory is recommended for a supply chain management (SCM) system. Building a flexible manufacturing system increases the total cost of the supply chain; for this reason, a discrete investment is important. For flexible production systems, production rate within a finite specific interval of production rate as work-in-process inventory is calculated. The aim of the supply chain is to reduce the total cost when demand during the lead time is a random variable with a normal distribution. A crashing cost is utilised to reduce the duration of lead time within the supply chain system. A model is proposed to obtain the optimal flexible production rate with the reduced total cost of the supply chain. A classical optimisation technique is employed to obtain the closed-form and quasi-closed-form solutions of the decision variables. An improved algorithm is designed to obtain the global minimum cost of SCM under the framework of a flexible production system. An illustrative numerical example and sensitivity analysis are given to test the model. A numerical study proves that this model obtains the minimum cost with the optimal decision variables.     

跨境VMI供货模式下生产-库存联合优化研究

研究基于跨境VMI(vendor managed inventory)供货模式下的生产-库存联合优化问题。以一个实际案例企业作为应用背景,比较了VMI供货模式和传统的供货模式在海运和空运2种运输方式下的不同特点及其对决策的影响。研究结果表明,对于案例企业而言,采用VMI供货模式的库存管理是可行的,考虑目前公司采用2种可选的运输模式,选择海运的总成本最低。通过对资金费用率、库存费用比率和缺货费用率进行灵敏度分析,探讨了不同环境变量对最优决策的影响。研究结果对跨境供应链多国生产型企业改善跨境物资采购和生产-库存决策有一定参考价值。     

Fuzzy scheduling of a build-to-order supply chain

The overwhelming majority of the literature in the area of supply chain planning and scheduling considers the traditional make-to-stock (MTS) environment. However, manufacturers of assembled products such as cars, computers, furniture, etc. adopt the build-to-order supply chain (BOSC) to become agile in a mass customization process in order to meet diversified customer requirements. In this paper we propose an integrated production–distribution planning model for a multi-echelon, multi-plant and multi-product supply chain operating in a build-to-order (BTO) environment. The uncertainties associated with estimation of the various operational cost parameters are represented by fuzzy numbers. The BOSC scheduling model is thus constructed as a mixed-integer fuzzy programming (MIFP) problem with the goal of reducing the overall operating costs related to component fabrication, procurement, assembling, inspection, logistics and inventory, while improving customer satisfaction by allowing product customization and meeting delivery promise dates at each market outlet. An efficient compromise solution approach by transforming the problem into an auxiliary multi-objective linear programming model is also suggested.     

A dynamic multi-plant lot-sizing and distribution problem

In this paper, we investigate a multi-plant, production planning and distribution problem for the simultaneous optimisation of production, inventory control, demand allocation and distribution decisions. The objective of this rich problem is to satisfy the dynamic demand of customers while minimising the total cost of production, inventory and distribution. By solving the problem, we determine when the production needs to occur, how much has to be produced in each of the plants, how much has to be stored in each of the warehouses and how much needs to be delivered to each customer in each period. On a large real data-set inspired by a case obtained from an industrial partner, we show that the proposed integration is highly effective. Moreover, we study several trade-offs in a detailed sensitivity analysis. Our analyses indicate that the proposed scenarios give the company competitive advantage in terms of reduced total logistics cost, and also highlight more possibilities that become available taking advantage of an integrated approach towards logistics planning. These abundant opportunities are to be synergised and exploited in an interconnected open global logistics system.     

The Integration Model of Closed-Loop Supply Chain Resource Allocation Considering Remanufacturing

Logistics resource planning is an integration model of materials requirement planning and distribution resource planning which is a resource allocation technology. It is a technology of satisfying both production material supply and resource allocation optimization which is based on inventory management. For the remanufacturing supply chain, recycling and rebuilding of products form a reverse materials movement loop which challenges the traditional logistics resource planning system. For the characteristics of reverse logistics of remanufacturing supply chain, we propose a closed-loop supply chain resource allocation model based on autonomous multi-entity. We focus on integration resource allocation model of materials requirement planning and distribution resource planning considering remanufacturing.     

周期可变下考虑多车型的库存路径优化研究

目的 研究基于供应商管理库存模式下，由一个供应商和多个零售商组成的二级供应链配送系统的库存路径优化问题，确定计划期内各配送周期的长度、数量，对供应链中库存策略与配送方案问题进行协调优化，使系统总成本最低。方法 考虑的成本包括库存持有成本、缺货成本和配送成本。为降低供应链系统的总成本，提出全新的周期可变策略。结果 采用遗传算法求解得出最佳方案。将不同策略的算例结果进行对比分析，结果表明周期可变策略与周期固定策略相比，系统总成本最低节约比例为1.7%，最高节约比例为42.3%。结论 通过对计划期内各配送周期的长度及数量进行划分调整可以有效地节约系统总成本，同时，采用多车型的配送方案明显优于采用同车型的配送方案。     

Vendor-managed inventory with consignment stock agreement for single vendor–single buyer under the emission-trading scheme

This paper presents a joint economic lot size (JELS) model for coordinated inventory replenishment decisions under the vendor-managed inventory (VMI) with consignment stock (CS) agreement and an emission-trading scheme. The paper assumes a single product that flows along a two-level supply chain system, with a single vendor and a single buyer. The total cost of the system is the performance measure, which is the sum of the vendor’s and the buyer’s total costs. The total cost includes the set-up and order costs, inventory holding costs, greenhouse gases (GHG) emissions tax and penalty costs. A mathematical model is proposed to determine: (1) the vendor’s production lot size quantity; (2) the number of shipments sent by the vendor to the buyer in a cycle; and (3) the production rate that minimises the total cost of the supply chain. Some numerical examples are carried out, as well as comparisons with the traditional JELS model for a classic two-level supply chain. Results show that the performance of the system is better when it is operated under a VMI with CS agreement, which is capable of reducing the traditional inventory holding costs and, for some values of given parameters, the GHG emissions tax and penalty costs.     

分割配送的生鲜产品库存-路径优化研究

目的 基于供应商管理库存策略,优化协调第三方物流（3rd Party Logistics,3PL）参与的二级供应链系统中库存补充与补货配送的关系,在满足配送需求的同时降低系统的库存和运输成本。方法 综合考虑3PL物流模式下的库存-路径系统中生鲜产品的运输距离、质量时间窗以及需求分割配送策略在时间上的调整等因素,以异质车队车辆行驶燃油成本、车辆调用固定成本、配送超时腐坏成本以及各零售商的库存成本为目标函数,建立多品种生鲜产品库存-路径优化模型。结果 通过改进的遗传算法计算并进行配送量调整优化,得到最终的生鲜配送方案,其系统总成本比配送量调整前减少了9.98%。结论 通过在时间上对配送量进行拆分调整可以有效地节约供应链系统总成本。     

Innovative vendor-managed inventory strategy exploiting interconnected logistics services in the Physical Internet

Traditional supply chain networks are often designed in the interests of a company. Once the network has been defined, the storage and distribution of goods are usually fixed and restricted within the network. This is assumed to be an inherent limit of current inventory control research. Instead of specialised hierarchical storage networks, this paper proposes an innovative vendor-managed inventory strategy exploiting the Physical Internet (PI), which is an open, universal, interconnected logistics system. In such a system, facilities and means of transport are shared and can be allocated according to demands of users. As a result, the PI allows users to stock anywhere in the network and also provides open multisourcing options for orders with on-demand warehousing services within the PI. Inventory decisions can be made dynamically by each player to minimise networkwide inventory levels. A non-linear, simulation-based optimisation model was developed for the vendors’ inventory decision-making when confronted with stochastic demands. A metaheuristic using simulated annealing was applied to solve the problem, and then, the optimised inventory decisions were validated using simulation. The results suggest that the proposed PI inventory model can reduce the total logistics cost while maintaining a comparable or better level of end customers’ services.     

汽车零部件生产物流中物料上线方式选择研究

目的为了降低拉动系统中的线边物料配送成本,提高内部物流供应效率。方法首先,运用ABCXYZ分析矩阵法,根据产品特性、存储成本、周期需求量、生产节拍等生产物流参数,确定出高量物料和低量物料;其次,分别对2种配送方式下的成本指标进行分解,建立不同上料模式产生的物流成本模型;最终,以物料消耗量和配送成本为原则,设计出合理的配送物料和看板物料的选择方式,并以LD公司为例对该选择逻辑进行验证。结果重新调整了EKP产品物料的上线方式,使样例中的13种物料配送成本减少了489.09元,总物料配送成本减少了7013.63元。结论研究结果对生产制造企业提高仓库对产线的响应速度,缩短产品周期,降低物料配送成本具有参考意义。     

The impact of cost structure on supply chain cash flow risk

Managing supply chain cash flow risk has become a crucial task for many cash-stressed businesses. Cash flows usually lag behind operating earnings and exhibit higher volatility than earnings, making them less predictable. Through the three components of the cash conversion cycle – days in inventory, receivables, and payables, this study investigates the impact of cost structure – cost ratios and cost compositions – on cash flow risk (standard deviation) and explains why and how management philosophies, such as Just-In-Time, and new production technologies, such as 3D printing, can lower cash flow risk by shortening days in inventory and shifting cost structure. An analytical model built on a simple demand process examines the basic relationship between cost structure and cash flow risk while a simulation approach studies the same relationship under a more general demand process with additional modelling considerations and a benchmark test. The simulation approach is applied on a publicly traded company’s financial data to demonstrate how supply chain process improvement can reduce the cash flow risk.     

A decomposition approach for the performance analysis of a serial multi-echelon supply chain

Over the last decade, supply chain coordination has attracted much attention in the context of industrial logistics systems, because of the role played in production support logistics. There is a growing interest in the analysis and measurement of performances, because performance analysis allows us to build supporting decision tools for the design, planning and management of the supply chain. This paper presents an analytical approach for performance analysis based on a decomposition principle. The approach is applied to a serial supply chain that consists of two levels of suppliers, a production plant and a distribution centre, and operates as a pull system. This configuration is typical for bulk materials such as grain. The method allows us to approximately calculate performance indicators (such as customer satisfaction and inventory levels) taking into account all the interactions between the different echelons of the supply chain. The accuracy of the approximations is confirmed by the results obtained via a simulation model. Numerical analysis allows us to outline interesting and non-intuitive behaviour of the performance indicators for different stages of the supply chain.     

Aggregate procurement,production, and shipment planning decision problem for a three-echelon supply chain using swarm-based heuristics

Supplier selection is deemed as a crucial strategic decision-making activity in building a competitive edge. Firms prefer to operate with a few trusted suppliers, selected from a bigger pool of vendors. The chosen suppliers are the ones whose commitments are best oriented in realising the business goals of the company. At the same time enterprise targets cannot be achieved in the absence of cost-effective inventory management policies. This has created the inevitable need for aggregate production and distribution planning. Even more competitive strategy would be integrating procurement planning with production-distribution scheduling. We address the problem of integrated procurement, production and shipment planning for a supply chain, spanning over three echelons. Supplier order scheduling is combined with a production-shipment planning process to realise a minimum cost operations policy. Two recently developed swarm heuristics are employed to search for the near optimal solution of the mathematical model, which is developed to capture the aggregate planning problem.     

Operations planning in a supply chain system with fixed-interval deliveries of finished goods to multiple customers

Raw material ordering policy and the manufacturing batch size for fixed-interval deliveries of finished goods to multiple customers play a significant role in economically managing the supply chain logistics. This paper develops an ordering policy for raw materials and determines an economic batch size for a product at a manufacturing center which supplies finished products to multiple customers, with a fixed-quantity at a fixed time-interval to each of the customers. In this model, an optimal multi-ordering policy for procurement of raw materials for a single manufacturing system is developed to minimize the total cost incurred due to raw materials and finished goods inventories. The carried over inventory of finished goods from the previous cycle is used as initial finished goods inventory, resulting in shifting the production schedule ahead for the next cycle. A closed-form solution to the problem is obtained for the minimal total cost. The algorithm is demonstrated for multiple customer systems.     

TOC-based performance measures and five focusing steps in a job-shop manufacturing environment

Theory of constraints (TOC) views a company as a set of interdependent processes working in harmony to achieve the profit goal of the company as a whole, and thus it emphasizes total system performance over localized measures to guide operational decisions. This paper demonstrates the usefulness of employing TOCbased global performance measures to make operational-decisions (e.g. product mix, continuous improvement, inventory management, production planning and scheduling) to strengthen the internal supply chain in a relatively complex manufacturing environment, i.e. a job shop. An ARENA-based simulation model is presented and a number of scenarios are discussed that provide insights regarding the characteristic features of TOC, such as goals and necessary conditions, performance measures, five-focusing steps for continuous improvement, and drumbuffer-rope scheduling. These insights will assist managers in making important decisions regarding approaches to successful TOC implementations, and will provide academics with a broad range of future research opportunities.     

订单式生产下汽车零配件企业采购决策研究

为解决传统JIT模式下供应链非主导的汽车零配件厂面临的巨大交付压力与高昂存货管理成本问题,基于MTO订单式生产下汽配厂的原材料供应现状,对其原材料进行两步分类得出3类原材料,分别建立以最小化存货成本的多周期动态规划模型,并推出其最优采购策略。最后,采用M企业实际运营数据进行对比分析,发现最优策略下的原材料存货周转天数显著缩短、库存成本显著降低,验证了优化策略的可行性及有效性。     

供应链管理环境下的单周期库存控制建模及优化

传统的库存控制理论已经不能够适应供应链管理的要求。在建立了供应链库存成本的组成模型的基础上对供应链管理中的单周期库存控制过程进行了深入的分析，建立了相应的数学模型，求出了最优解。     

考虑修复成本的逆向物流多级库存优化研究

通过对逆向物流多级库存的提法引入,提出了逆向物流多级库存总成本最小化问题．在对产品召回的条件下回收系统模型图简化的基础上,提出了考虑修复成本的逆向物流的多级库存成本优化模型,并用MATLAB编程计算实际算例,得出总成本的优化值．研究结果表明,考虑了修复成本的逆向物流多级库存成本优化更具实际应用意义．