Developing a coordinated vendor–buyer model in two-stage supply chains with stochastic lead-times

This paper develops an approach to determine the optimal production and shipment policy for an integrated vendor–buyer problem. The vendor manufactures the product in batches at a finite rate and ships the output to the buyer. All shipments to the buyer are equal-sized batches. Despite previous papers in the literature, we assume that the supply lead-time between vendor and buyer is stochastic and shortage is also allowed. The objective is to minimize the expected total cost of both buyer and vendor. We derive the expected annual integrated total cost function and propose an analytic solution procedure to determine the optimal policy. To illustrate the significance of cost-reduction of the integrated approach in comparison with independent decisions by buyer or vendor, some numerical examples are also presented.     

Two-echelon supply chain inventory model with controllable lead time and service level constraint

This paper considers a two-echelon supply chain inventory problem consisting of a single-vendor and a single-buyer. In the system under study, a vendor produces a product in a batch production environment and supplies it to a buyer facing a stochastic demand, which is assumed to be normally distributed. Also, buyer’s lead time is controllable which can be shortened at an added cost and all shortages are backordered. A model has been formulated for an integrated vendor–buyer problem to jointly determine the optimal order quantity, lead time and the number of shipments from the vendor to the buyer during a production cycle while minimizing the total expected cost of the vendor–buyer integrated system. It is often difficult to estimate the shortage cost in inventory systems. Therefore, instead of having a shortage cost term in the objective function, a service level constraint (SLC) is included in the model that requires a certain proportion of demands to be met in each cycle. An efficient procedure has been suggested to find the bounds on number of shipments and then, an algorithm is developed to obtain the optimal solution of the proposed model. A numerical example is included to illustrate the algorithmic procedure and the effects of key parameters are studied to analyze the behavior of the model. Finally, the savings of buyer and vendor are investigated from implementation of joint optimization model over the model in which they minimize their own cost independently.     

Cost allocation model for optimizing supply chain inventory with controllable lead time

The coordination issue of a decentralized supply chain composed of a vendor and a buyer is considered in this paper. The vendor offers a single product to the buyer and the lead time can be controllable with adding crashing cost. Two supply chain inventory models with controllable lead time under different decision modes are considered, one is proposed under decentralized model based on Stackelberg model, the other is proposed under centralized model of the integrated supply chain. The solution procedures are also suggested to get the optimal solutions of these two models. In addition, an asymmetric Nash bargaining model based on satisfaction level is also developed to get the best cost allocation ratio between the vendor and the buyer by taking their individual rationalities into consideration. The results of numerical example show that shortening lead time reasonably can reduce inventory cost and the cost allocation model based on satisfaction level developed in this paper is effective.     

Supplier–buyer models for the bargaining process over a long-term replenishment contract

This paper presents supplier–buyer models to describe the bargaining process between a supplier and a buyer over a long-term replenishment contract. Two different models are developed: one for the situation where the supplier has a superior bargaining power over the buyer, and the other for the reverse situation. For each model, a method is derived to find the best strategy of each agent via analysis based on a game-theoretic approach. The solution found by the method is verified to be the Nash Equilibrium of each model. The system costs of the models are compared to determine the economic implications of the results.     

An integrated vendor–buyer inventory model with backorder price discount and effective investment to reduce ordering cost

The single-vendor single-buyer integrated production inventory system has been an object of study for a long time, but little is known about the effect of investing in reducing ordering cost on the integrated inventory models with backorder price discount and variable lead time. The purpose of this article is to investigate in the continuous review model with backorder price discount and variable lead time to effectively increase investment and to reduce the joint expected annual total cost. The integrated strategy discussed here is one in which the buyer orders a quantity, then the vendor produces n times order quantity in each production cycle, in order to reduce setup cost. In addition, the buyer offers backorder price discounts to the customers that may motivate the customers’ desire for backorders, and buyer ordering cost can be reduced through effective investment. An integrated inventory model is established to find the optimal solutions of order quantity, ordering cost, backorder price discount, lead time, and the number of shipments from the vendor to the buyer in one production run, so that the joint expected annual total cost incurred has the minimum value. Furthermore, numerical examples are used to demonstrate the benefits of the model.     

Supply chain coordination with defective items and quantity discount

This study develops an integrated inventory system involving defective items and quantity discount for optimal pricing and ordering strategies. The model analysed in this study is one in which the buyer orders a quantity, the vendor produces more than buyer's order quantity in order to reduce set-up cost, and then he/she offers an all-units quantity discount to the buyer. Our objective is to determine the optimal order quantity, retail price, mark-up rate, and the number of shipments per production run from the vendor to the buyer, so that the entire supply chain joint total profit incurred has a maximum value. Furthermore, an algorithm of finding the optimal solution is developed. Numerical examples are provided to illustrate the theoretical results.     

A manufacturer–buyer integrated inventory model with stochastic lead times for delivering equal- and/or unequal-sized batches of a lot

Although the subject of manufacturer–buyer integrated inventory management with deterministic lead times has received a lot of attention from researchers, the corresponding problem with stochastic lead times has been given comparatively little consideration. Recently, it has been treated in the case of an exponential distribution of lead times with the lot transferred in equal-sized batches (sub-lots). In this treatment the buyer orders the next batch when his/her stock level falls to a certain reorder point, allowing for shortages and complete backordering. The total cost benefit of solving the problem using an integrated inventory system instead of independent ones had been demonstrated. However, rather than an exponential distribution, a normal distribution of lead times seems to provide a better fit to the problem. Moreover, synchronization of the integrated production flow by generalizing the method of transferring batches of the lot might lead to a lower total cost. Based on these notions, we develop here a manufacturer–buyer integrated inventory model with a normal distribution of lead times for delivering equal- and/or unequal-sized batches of a lot. Then a solution technique to the model and hence a solution algorithm are presented. The potential benefit of the present method is illustrated with solutions of some numerical problems. The sensitivities of the solutions to variations in the parameter values are also studied.     

An operational policy for an integrated inventory system under consignment stock policy with controllable lead time and buyers’ space limitation

This paper aims to enable the decision maker of an integrated vendor–buyer system, under Consignment Stock (CS) policy, to make the optimal/sub-optimal production/replenishment decisions where the buyer places a space limitation to the vendor and the lead-time is controllable with an extra investment. Within any production cycle, the vendor produces at a finite rate and ships the outputs to the buyer with a number of equal-sized lots. With a long-term consignment stock agreement, the vendor takes responsibility to maintain a certain inventory level in the buyer's warehouse. Some of the shipments are delayed so that the buyer's inventory does not go beyond the capacity limitation. The buyer compensates the vendor after the complete consumption of the products. The holding cost consists of a storage component and a financial component. Two constraint four-variable non-linear integer optimization models are established wherein the buyer space limitation is considered. Because the developed models are mathematically very difficult to solve, three doubly hybrid meta-heuristic algorithms are employed to solve the models. The computational results show that one of these three algorithms works very well both in the sense of the success rate and the mean CPU time. The analysis of the computational example also reveals the quantitative effects the buyer space limitation may have to the annual joint total expected cost (JTEC) of the integrated system.     

An integrated production–distribution inventory system involving probabilistic defective and errors in quality inspection under variable setup cost

This paper presents a probabilistic defective vendor–buyer integrated inventory model with the consideration of quality inspection errors at the buyer's end and setup cost as function of capital investment. An integrated inventory model is established to find the optimal solutions of lot size, setup cost, and the total number of shipments from the vendor to the buyer in one production run, so that the joint expected total cost incurred has the minimum value. We consider three types of continuous probabilistic defective function to find the associated cost of the system. The expected total cost function is derived for each of these three distributions, its convexity is proved via differential calculus. An efficient iterative algorithm is designed to obtain the optimal solution of the model. The computational effort and time are small for the proposed algorithm and it is simple to implement. Numerical examples and sensitivity analysis are used to demonstrate the application and the performance of the proposed methodology. The computational results indicate that if we make decisions with the capital investment in reducing setup cost, it will help to lower the system cost, and we obtain a significant amount of savings to increase the competitive edge in business.     

An optimization approach for joint pricing and ordering problem in an integrated inventory system with order-size dependent trade credit

Under a business trading environment, it is common for the trade credit to depend on the order size. Therefore, it is important to discuss the single-supplier and single-buyer supply chain problem which includes order-size dependent trade credit. In this study, an integrated inventory model with a price sensitive demand rate, determining jointly economic lot size of the buyer’s ordering and the supplier’s production batch, are developed to maximize the total profit per unit time. An efficient algorithm is provided to obtain the optimal solution, and then numerical examples are presented to illustrate the theoretical results. Finally, the comparison between whether an optimal solution is jointly or independently determined is also provided.     

Supply chain coordination model with controllable lead time and service level constraint

We consider the coordination issue in a decentralized supply chain composed of a vendor and a buyer in this paper. The vendor offers a single product to the buyer who is faced with service level constraint. In addition, lead time can be reduced by added crashing cost. We analyze two supply chain inventory models. The first one is developed under decentralized mode based on Stackelberg model, the other one is developed under centralized mode of the integrated supply chain. The solution procedures are also provided to get the optimal solutions of these two models. Finally, a price discount mechanism is proposed to induce both the vendor and the buyer to accept the centralized model. The feasibility and efficiency of the proposed models are manifested by numerical examples and some managerial implications are highlighted.     

考虑损失规避型供应商的VMI 供应链协调

给出损失规避型供应商和风险中性零售商组成的二级VMI供应链批发价格契约与协调的理论分析.主要结论是:损失规避型供应商的最优产品生产量可能小于(等于或大于)风险中性的供应商的最优产品生产量,且最优产品生产量为单位剩余产品净残值(单位缺货成本)的增函数、单位库存成本的减函数、一定条件下的单位批发价格(单位生产成本)的增函数或减函数;批发价格契约在一定条件下可使二级VMI供应链达到协调.     

The consignment stock of inventories in coordinated model with generalized policy

In this paper, coordination between a single vendor (or manufacturer) and a buyer (or retailer) via the delivery schedule in a production and distribution system is presented. A continuous deterministic model with centralized decision process is developed. To satisfy the buyer’s demands, the product is delivered in discrete batches from the vendor’s stock to the buyer’s stock and all shipments are realized instantaneously. A more general type of consignment stock (CS) policies for the vendor–buyer integrated production–distribution model is analyzed. Our model does not require equal in size shipments. The inventory patterns and the cost structure of production distribution cycles (PDC) are described in different scenarios. A comparative study of the results shows that the generalized CS policies perform better. Considering CS-policies Braglia and Zavanella (2003) ask about a possibility of cost reduction by delaying a number of late deliveries. Unfortunately, a negative answer was given by Zanoni and Grubbström (2004). We verify this problem to obtain a positive answer in more general setting. A solution procedure is developed to find optimal generalized CS-policy for the problems with nonequal and equal in size deliveries. Optimal solutions are found and illustrated with numerical examples.     

Two-echelon fuzzy stochastic supply chain for the manufacturer–buyer integrated production–inventory system

This paper deals with two-echelon integrated procurement production model for the manufacturer and the buyer integrated inventory system. The manufacturer procures raw material from outside suppliers (not a part of supply chain) then proceed to convert it as finished product, and finally delivers to the buyer, who faces imprecise and uncertain, called fuzzy random demand of customers. The manufacturer and the buyer work under joint channel, in which a centralized decision maker makes all decisions to optimize the joint total relevant cost (JTRC) of entire supply chain. In this account, in one production cycle of the manufacturer we determine an optimal multi-ordering policy for the buyer. To be part of this, we first derive the JTRC in stochastic framework, and then extend it in fuzzy stochastic environment. In order to scalarize the fuzzy stochastic JTRC, we use an evaluation method wherein randomness is estimated by probabilistic expectation and fuzziness is estimated by possibilistic mean based on possibility evaluation measure. To derive the optimal policies for both parties, an algorithm is proposed. A numerical illustration addresses the situations of paddy procurement, conversion to rice and fulfillment of uncertain demand of rice. Furthermore, sensitivity of parameters is examined to illustrate the model and algorithm.     

Vendor–buyer inventory models with trade credit financing under both non-cooperative and integrated environments

Most researchers studied vendor–buyer supply chain inventory policies only from the perspective of an integrated model, which provides us the best cooperative solution. However, in reality, not many vendors and buyers are wholly integrated. Hence, it is necessary to study the optimal policies not only under an integrated environment but also under a non-cooperative environment. In this article, we develop a supply chain vendor–buyer inventory model with trade credit financing linked to order quantity. We then study the optimal policies for both the vendor and the buyer under a non-cooperative environment first, and then under a cooperative integrated situation. Further, we provide some numerical examples to illustrate the theoretical results, compare the differences between these two distinct solutions, and obtain some managerial insights. For example, in a cooperative environment, to reduce the total cost for both parties, the vendor should either provide a simple permissible delay without order quantity restriction or offer a long permissible delay linked order quantity. By contrast, in a non-cooperative environment, the vendor should provide a short permissible delay to reduce its total cost.     

Optimal transfer,ordering and payment policies for joint supplier–buyer inventory model with price-sensitive trapezoidal demand and net credit

This study aims at formulating an integrated supplier–buyer inventory model when market demand is variable price-sensitive trapezoidal and the supplier offers a choice between discount in unit price and permissible delay period for settling the accounts due against the purchases made. This type of trade credit is termed as ‘net credit’. In this policy, if the buyer pays within offered time M₁, then the buyer is entitled for a cash discount; otherwise the full account must be settled by the time M₂; where M₂ > M₁ ? 0. The goal is to determine the optimal selling price, procurement quantity, number of transfers from the supplier to the buyer and payment time to maximise the joint profit per unit time. An algorithm is worked out to obtain the optimal solution. A numerical example is given to validate the proposed model. The managerial insights based on sensitivity analysis are deduced.     

Supplier–retailer inventory coordination with credit term for inventory‐dependent and linear‐trend demand

In this paper, a nonintegrated and collaborative replenishment policy is considered, respectively, which incorporates varying demand depending on both inventory level and time during the finite planning horizon. For additional cost savings realized from coordination, the paper adopts trade credit as a cost‐saving shift means and introduces a brand new parameter, that is, credit period rate. Then, the equitable credit period rate is determined, and different values of the credit period rate reflect the allocation of additional cost savings between the supplier and retailer. Furthermore, the conditions for the existence and uniqueness of an optimal solution are proved for the nonintegrated and collaborative replenishment policy, and an efficient solution procedure is developed to determine the optimal results and coordination of the inventory model. Finally, several numerical examples are provided to illustrate the proposed strategy and algorithm, and the sensitivity analysis of the optimal solution with respect to each parameter is presented. The sensitivity analysis suggests that the size of the credit period rate has a strong relationship with the supplier's and retailer's inventory cost (including capital cost) and setup cost. In real‐life situations, this proposed strategy may be applied to some consumer products in the growth phase or best‐selling consumer goods, etc.     

Deteriorating item inventory model with shortage due to supplier in an integrated supply chain

The aim of this paper is to develop an inventory model for deteriorating items with a shortage occurring at the supplier involving a supply chain between the producer and buyer. A numerical example is used to illustrate the model and demonstrate that integrated decisions are more cost-effective compared with independent decisions from the supplier, producer or buyer. The optimal number of deliveries is derived with the minimal joint total cost from the integrated viewpoint. This study compares cases with and without shortages. A sensitivity analysis is given to explore the effect from a supplier shortage.     

A multiple-vendor single-buyer integrated inventory model with a variable number of vendors

Supply chain management is concerned with the coordination of material and information flows in multi-stage production systems. A closer look at the literature reveals that previous research on the coordination of multi-stage production systems has predominantly focused on the sales side of the supply chain, whereas problems that arise on the supply side have often been neglected. This article closes this gap by studying the coordination of a supplier network in an integrated inventory model. Specifically, we consider a buyer sourcing a product from heterogeneous suppliers and tackle both the supplier selection and lot size decision with the objective to minimise total system costs. First, we provide mathematical formulations for the problem under study, and then suggest a two-stage solution procedure to derive a solution. Numerical studies indicate that our solution procedure reduces the total number of supplier combinations that have to be tested for optimality, and that it may support initiatives which aim on increasing the efficiency of the supply chain as a heuristic planning tool.     

Investing in lead-time variability reduction in a collaborative vendor–buyer supply chain model with stochastic lead time

This study deals with investing in lead-time variability reduction problems for the integrated vendor–buyer supply chain system with partial backlogging under stochastic lead time. We consider that lead time variability can be reduced through further investment; more specifically, a logarithmic investment function is used that allows investment to be made to reduce lead-time variability. By using the proposed supply chain model, considerable savings can be achieved to increase the competitive edge. The objective is to derive the optimal production/ordering strategy, and the best investment policy to minimize joint total cost. A computer code using the software, Mathematica, is developed to derive the optimal solution. Furthermore, we discuss the sensitivity of the optimal solution together with the changes of the values of the parameters associated with the model for decision-making. Various numerical examples are given to illustrate the results.