Finite horizon planning for a production system with permitted shortage and fixed-interval deliveries

Raw material ordering policy and the manufacturing batch size for frequent deliveries of finished goods for a finite horizon plays a significant role in managing the supply chain logistics economically. This research develops an ordering policy for raw materials and determines an economic batch size for a product in a manufacturing system that supplies finished products to customers for a finite planning horizon. Fixed quantities of finished products are delivered to customers frequently at a fixed interval of time. In this model, an optimal multi-ordering policy for procurement of raw materials and production cycle time for a two-stage production and supply system is developed to minimize the total cost incurred due to raw materials and finished goods inventories. The problem is then extended to compensate for the lost sales of finished products. A closed-form solution to the problem is obtained for the minimal total cost. A lower bound on the optimal solution is also developed for problem with lost sale. It is shown that the solution and the lower bound are consistently tight.     

An integrated production and inventory model for a system comprising an assembly supply chain and a distribution network

This study investigates the production and inventory problem for a system comprising an assembly supply chain and a distribution network. A uniform lot size is produced uninterruptedly with a single setup at each production stage. Equal-sized batch shipment policy is applied to the whole system and the number of batches can be varied. All retailers have agreed on a joint replenishment policy with a common replenishment cycle. The objective is to determine the optimal common replenishment cycle, the number of batches of each production stage and retailer, all of which minimises the integrated total cost. Moreover, a new concept is introduced; namely, critical replenishment cycle. The replenishment cycle division (RCD) and recursive tightening (RT) methods are then developed to obtain the optimal solutions to the subject problem. Two theorems are verified to ensure the solutions obtained by the RCD and RT methods reaching the global optimum. An example is presented to illustrate the procedures involved in the RCD and RT methods.     

Joint optimization of pricing and planning decisions in divergent supply chain

In divergent supply chains, such as in the oil industry, processing raw materials results in an outflow of multiple products. Final products are stored at international depots, from where they are ready to be shipped to the markets. Even if one company controls the entire chain, when production and sales organizations are decoupled, a relevant problem is to determine the internal prices of products at depots for achieving coordination. We propose an optimization model involving pricing and production decisions, and several constraints commonly used in divergent chains. In our approach, the producer incorporates the sellers’ behavior by expressing demand as a function of the internal price. As a result, our model serves as a coordination mechanism in trying to get an overall coordinated integrated solution in a decoupled reality. Numerical examples in single and multiple periods problems show the advantages of our approach over cost‐based methods.     

An optimal batch size for a production system operating under periodic delivery policy

A manufacturing system that procures raw materials from suppliers in a lot and processes them into a finished product is considered in this research. An ordering policy is proposed for raw materials to meet the requirements of a production facility which, in turn, must deliver finished products demanded by outside buyers at fixed points in time. First, a general cost model is formulated considering both raw materials and finished products. Then, using this model, a simple procedure is developed to determine an optimal ordering policy for procurement of raw materials, and the manufacturing batch size, to minimize the total cost of meeting customer demands in time. The dependent relationships between production batch size and rawmaterial purchasing quantity, and various delivery patterns considered in recent literature are critically reviewed. The quality of the solution is evaluated. Numerical examples are provided.     

The governing dynamics of supply chains: The impact of altruistic behaviour

This paper analyses an infinite horizon two-echelon supply chain inventory problem and shows that a sequence of the optimum ordering policies does not yield globally optimal solutions for the overall supply chain. First-order autoregressive demand pattern is assumed and each participant adopts the order-up-to (OUT) policy with a minimum mean square error forecasting scheme to generate replenishment orders. To control the dynamics of the supply chain, a proportional controller is incorporated into the OUT policy, which we call a generalised OUT policy. A two-echelon supply chain with this generalised OUT policy achieves over 10% inventory related cost reduction. To enjoy this cost saving, the attitude of first echelon player to cost increases is an essential factor. This attitude also reduces the bullwhip effect. An important insight revealed herein is that a significant amount of benefit comes from the player doing what is the best for the overall supply chain, rather than what is the best for local cost minimisation.     

Cost performance dynamics in lean production leveling

Balancing of production systems is one of the main lean manufacturing principles as it reduces in-process storage and related forms of waste. A dynamic systems approach is proposed to investigate challenges of implementing production leveling and associated costs. A lean cell producing at takt time is modeled using system dynamics. The model captures various lean tools influencing production leveling and their implications. Comparative cost analysis between various leveling implementation policies for stochastic demand with multiple products is conducted. Results showed that determining the most feasible leveling policy is highly dictated by both the cost and limitations of capacity scalability. In addition, delivery sequence plans of different products/parts needed to achieve mix leveling and lot sizes affect the feasible production leveling policy while implementing lean principles. The developed model and insights gained from the results can help lean manufacturing practitioners to better decide when and how to implement production leveling as well as determine both production lots sizes and sequence. They also emphasize the importance of cost analysis as assisting decision support tool in the trade-off required between the benefits of different levels of lean policies and their associated cost.     

GBOM-oriented management of production disruption risk and optimization of supply chain construction

A generic bill-of-materials (GBOM) describes demand for materials and their proportional relations to a family of products. Supply chain constructed from the perspective of the GBOM is able to respond swiftly to market demand and lean production can be achieved by managing the total cost of supply chain effectively. Based on the GBOM, this paper examines the control of production disruption risk related to supply chain and investigates the uncertainty of production in supply chain enterprises for the purpose of achieving optimal profits in supply chain. As the production disruption risk is controlled at a certain level, the selection model of supply chain partners, which is specific and more feasible, can be constructed. A combination of random simulation and neural network is deployed to approximate uncertain function, and genetic algorithm and simulated annealing arithmetic are also used to approximately achieve the optimal scheme of supply chain construction in the context of uncertainty.     

A flexible agent system for change adaptation in supply chains

The importance of supply chain management is increasing with globalization and the advancement of electronic business. Supply chains are dynamic due to frequent changes in suppliers, customers, and products. However, information systems for supply chains are not flexible enough to adapt to the changes, requiring high cost and time for re-implementation and re-customization. This paper suggests a flexible agent system for supply chains that can adapt to the changes in transactions introduced by new products or new trading partners. The flexible agent system consists of an interpretable conversation policy model, a procedure for exchanging new conversation policies, and a mechanism for actual transactions with newly acquired conversation policies. By using the flexible agent system, formation of supply chains becomes more robust to the dynamic changes. To show how the approach can be realized, a PC supply chain application is illustrated with a prototype agent platform.     

考虑提前期压缩的Newsvendor型产品供应链协调模型

在假定制造商的单位生产成本是关于提前期的减函数的前提下,将提前期视为可控决策变量,建立了带有提前期压缩的Newsvendor型产品供应链协调模型,讨论了提前期压缩对供应链及其成员收益的影响,并利用由回购和回扣/惩罚所组成的联合契约实现了供应链的协调.数值仿真分析结果验证了结论的正确性.     

Vertical pricing competition in supply chains: the effect of production experience and coordination

We consider a two‐echelon supply chain consisting of a single supplier (producer) and a retailer. The supplier determines the wholesale price with a production cost decreasing with experience. The retailer orders products from the supplier to meet demands. Negative effects of a vertical competition in static supply chain models are typically attributed to a double marginalization. Using an intertemporal supply chain problem, defined by a differential game, we show that in addition to the “cost” of double marginalization, the margin gained from reducing production costs affects the supply chain performance as well. In our analysis, performance is shown to deteriorate even more than the deterioration observed in static problems with no learning (experience). To improve the performance, we provide a time‐variant version to the well‐known, pure, two‐part tariff strategy, which in its dynamic framework may coordinate the supply chain only partially. Efficient coordination in a supply chain is shown to be possible if a mixed two‐part tariff strategy is employed, however.     

Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

The Bass model is a very successful parametric approach to forecast the diffusion process of new products. In recent years, applications of the Bass model have been extended to other operational research fields such as managing customer demands, controlling inventory levels, optimizing advertisement strategies, and so forth. This study attempts to establish an application for optimizing manufacturers’ production plans in a three-stage supply chain under the Bass model’s effects on the market. The supply chain structure considered in this research is similar to other common supply chains comprised of three stages, namely retailer, distributor and manufacturer. The retailer stage has to handle customer demands following the Bass diffusion process. Market parameters and essential information are assumed to be available and ready for access. Each stage is expected to determine its inventory policy rationally. That is, each stage will attempt to maximize its own profits. These decisions will back-propagate their effects to upper stages. This study adopts a dynamic programming approach to determine the inventory policies of each stage so as to optimize manufacturers’ production plans.     

Modelling and analysis of inventory replenishment for perishable agricultural products with buyer–seller collaboration

In this article, we study the inventory replenishment model for perishable agricultural products in a simple two-level supply chain. Collaborative forecasting is introduced into the inventory replenishment decisions to avoid overstocking and understocking of agricultural products, and to maximise profits. We analyse the model with ordering cost, holding cost, shortage cost, deterioration cost and opportunity lost cost of perishable agricultural products. Extensive numerical analysis is carried out to study the performance of the inventory policy. The optimal replenishment policy that minimises the total cost can be obtained from the model. It has demonstrated that the supply chain cost decreases with supplier and retailer's collaborative forecasting.     

Intra-supply chain system with multiple sales locations and quality assurance

The emergence of the global economy has transformed the interdepartmental nature of a transnational enterprise into a highly collaborative oriented team. This transformation enables the enterprise to lower its transaction and coordination costs and increase its competitive advantage in the global market. This study investigates such a so-called intra-supply chain system that exists in present-day transnational firms, wherein a single production unit manufactures products to meet the demands of multiple regional sales offices and incorporates quality assurance in its production. The objective of the present study is to determine an optimal production quantity and shipment policy that minimizes the integrated production–inventory–delivery costs for the intra-supply chain system. In this study, considerations related to a product’s quality assurance include inspection for quality, rework of defective items and failure in rework. Delivery of the finished products starts when quality of the entire production lot is assured. Multi-shipment policy is used to synchronously transport finished items to multiple locations for satisfying customer demands in each cycle. Mathematical modeling along with Hessian matrix equations is employed to solve the proposed intra-supply chain system. A numerical example with a discussion and cost-benefit analysis of outsourcing work to an external distributor is presented to demonstrate the practical applicability of the obtained results.     

基于VMI&TPL 供应链的单供应商两制造商补货策略

供应商与第三方物流合作实施供应商管理库存,采用共同补货转运策略( , , )为地理位置相邻的两制造商供应零部件,并通过两制造商初期库存之差 来分配库存,允许制造商相互转运.首先分析随机需求下两制造商总库存的变化情况,求解共同补货转运策略( , , )下的库存、缺货数量和转运数量及其随各控制值变化的性质;然后,通过算例将提出的共同补货转运策略与供应商单独为各制造商补货的策略进行比较;最后,考察不同参数对共同补货转运策略效果的影响.     

Determining the production lot size with a heuristic inspection policy for controlling the quality of input materials and products

This study simultaneously determines the optimal production lot size and an inspection policy for input materials and products, where an unreliable process produces products with a discrete general shift distribution. This work proposes a heuristic inspection policy for materials and products, by first obtaining the inspection range for the input material without considering product inspection, and by further determining the product inspection range based on the obtained range of the input material inspection. The optimal inspection policy shows that common policies of no or full inspection are never optimal. This study includes the optimal production lot size based on the obtained inspection policy. Numerical examples demonstrate the impacts of input quality level, process reliability and unit nonconforming cost on the optimal solution, which adopts a discrete Weibull shift distribution to model the process failure time. Finally, this study addresses the conclusions.     

Decision making procedure of demand satisfaction and production policy for capacitated production systems

This paper develops a reliability-based decision making procedure for production systems to (i) evaluate the system reliability and (ii) determine the reliable production policy. The production system is represented as a capacitated production network (CPN) for system reliability evaluation, in which the system reliability is defined as the probability of demand satisfaction. The decision making to determine a reliable production policy is based on the derived system reliability. Two layouts are considered in this paper: the first layout is for the CPN with parallel lines; while the second layout is for the CPN with joint lines. Transformation and decomposition techniques are proposed to generate all minimal capacity vectors that workstations should provide to satisfy demand. In terms of the minimal capacity vectors, the system reliability is derived by applying the recursive sum of disjoint products (RSDP) algorithm. A case study in the context of footwear production system is utilized to demonstrate the decision making procedure.     

Coordinating the ordering and advertising policies for a single-period commodity in a two-level supply chain

This study deals with the news-vendor problem to the case of a two-level supply chain consisting of one manufacturer and one retailer, and investigates the combined effects of the cooperative advertising mechanism, the return policy and the channel coordination. The manufacturer and the retailer could maintain the potential market size by making some marketing expenditures on some national brand names and invest in local advertising, but with diminishing returns. The decision problem facing the profit-oriented entities in the supply chain is to determine the optimal advertising and inventory policies for maximizing their own profit. Both the non-cooperative policy and the cooperative policy are formulated to offer structural and quantitative insights into the interplay between upstream and downstream entities of the supply chain. In addition, the implications of a profit-sharing mechanism based on achieving a win–win relationship of the channel members was also proposed.     

An integrated approach for logistic and vendor managed inventory in supply chain

In this paper, a quaternary policy system towards integrated logistics and inventory aspect of the supply chain has been proposed. A system of multi retailers and distributors, with each distributor following a unique policy, will be analysed. The first policy is continuous time replenishment policy where the retailers’ inventory is replenished in every time interval. In the next three policies, inventory of the retailers will be replenished by some definite policy factors. The vendor managed inventory (VMI) system is used for updating the inventory of the retailers. An order-up-to policy (q, Q) is used for updating the inventory of distributors. Total erstwhile demands to the retailer will be used to determine the amount of inventory acclivity. Furthermore, the distributors will be sending the delivery vehicles to few fellow retailers who are shortlisted according to the policy, followed by the retailers and associated distributors. On the basis of random demand that the retailers are facing from end customers and the total demand that has incurred in the supply chain, products are unloaded to the selected retailers from the delivery vehicle. The path of the delivery vehicle is retrieved by dynamic ant colony optimization. In addition, a framework has been developed to measure the end-customer satisfaction level and total supply chain cost incorporating the inventory holding cost, ordering cost and the transportation cost. The framework has been numerically moulded with different settings to compare the performance of the quadruplet policies.     

Coordinated ordering decisions for products with short lifecycle and variable selling price

The supplier–buyer coordination is an important policy in the supply chain management. The buyer in the two-echelon inventory system with regular selling season has to face the uncertainty of customer demand, supplier’s delivery time and variable price change. At the same time, the supplier has to consider the inventory holding and delay cost. The objective of this study is to develop an integrated supply chain strategy for products with short lifecycle and variable selling price to entice cooperation. The strategy must provide a win–win situation for both the supplier and the buyer. A numerical case example, sensitivity analysis and compensation mechanism are given to illustrate the model.     

A production base-stock policy for recycling supply chain management in the presence of uncertainty

This study focuses on solving master planning problems for a recycling supply chain with uncertain supply and demand. A recycling supply chain network includes collectors, disassemblers, remanufacturers, and redistributors working from the collection of returned goods to the distribution of recovered products to the market. The objective of this study is to maximize the total profit of the entire recycling supply chain. Considering the stochastic property of the recycling supply chain, this study institutes stocking and processing policies for each member of the recycling supply chain to better respond to unknown future demand. We propose a heuristic algorithm called stochastic recycling process planning algorithm (SRPPA) to address master planning problems in the recycling supply chain and its supply and demand uncertainties. The main SRPPA process consists of three phases. In the leader determination phase, SRPPA identifies the most important node as the leader of the recycling supply chain. In the candidate policy set generation phase, SRPPA defines the search range for the inventory policy and forms the candidate policy sets based on the characteristics of the leader. In the best policy set selection phase, SRPPA constructs the simulation process for each inventory policy candidate to identify the best policy set. A scenario analysis is then presented to show the effectiveness and efficiency of SRPPA.