随机需求下基于供应中断的备份供应商决策分析

假定需求服从随机分布,研究由零售商主导的供应链中,采用一个战略供应商和一个备份供应商模式,零售商与备份供应商通过能力期权建立订货契约:首先,零售商向备份供应商预订能力,支付预订成本;接着,向战略供应商订货,如果没有发生突发事件则其供货量等于订货量,否则供货量变为零;然后,零售商基于战略供应商的供货量和备份供应商的能力预订确定向备份供应商的订货量,支付执行成本;最后,零售商用战略供应商和备份供应商的总供货量满足顾客需求。备份供应商在考虑自己的能力维持成本和制造成本后决定是否接受零售商提供的能力期权契约。针对零售商可选择的四种不同策略,求得采取不用策略所满足的条件,并给出相应的最优订货量、能力预订量和能力执行量和最优利润等的解析解。     

A single-period inventory placement problem for a supply chain with the expected profit objective

Consider the expected profit maximizing inventory placement problem in an N-stage, supply chain facing a stochastic demand for a single planning period for a specialty item with a very short selling season. Each stage is a stocking point holding some form of inventory (e.g., raw materials, subassemblies, product returns or finished products) that after a suitable transformation can satisfy customer demand. Stocking decisions are made before demand occurs. Because of delays, only a known fraction of demand at a stage will wait for shipments. Unsatisfied demand is lost. The revenue, salvage value, ordering, shipping, processing, and lost sales costs are proportional. There are fixed costs for utilizing stages for stock storage. After characterizing an optimal solution, we propose an algorithm for its computation. For the zero fixed cost case, the computations can be done on a spreadsheet given normal demands. For the nonnegative fixed cost case, we develop an effective branch and bound algorithm.     

Optimal policies for inventory systems with discretionary sales, random yield and lost sales

We determine replenishment and sales decisions jointly for an inventory system with random demand, lost sales and random yield. Demands in consecutive periods are independent random variables and their distributions are known. We incorporate discretionary sales, when inventory may be set aside to satisfy future demand even if some present demand may be lost. Our objective is to minimize the total discounted cost over the problem horizon by choosing an optimal replenishment and discretionary sales policy. We obtain the structure of the optimal replenishment and discretionary sales policy and show that the optimal policy for finite horizon problem converges to that of the infinite horizon problem. Moreover, we compare the optimal policy under random yield with that under certain yield, and show that the optimal order quantity （sales quantity） under random yield is more （less） than that under certain yield.     

促销努力成本信息不对称下供应链回购契约

在由一个供应商和一个销售商构成的二级供应链,假设市场需求受到销售商的促销努力水平的影响,销售季节到来之前,销售商根据促销成本和收益决定最优促销努力水平和订货量。在促销成本不可观测时,利用委托代理理论研究信息不对称时如何通过回购契约揭示真实的促销努力成本。研究结果表明销售商有动机将努力促销成本报高,为了吸引销售商显示真实的促销努力成本,供应商必须付出额外的信息租金,随促销成本增大,销售商通过虚报高成本获得的利润减小,故需要揭示真实成本信息所付出的信息租金随之减小。由于信息租金的付出,导致了非效率现象的产生,使得销售商的最优订货量和促销努力水平均小于完全信息下系统的最优水平,只能得到帕累托改进的次优结果。     

An inventory model with partial backordering and unit backorder cost linearly increasing with the waiting time

As the implementation of JIT practice becomes increasingly popular, each echelon in a supply chain tends to carry fewer inventories, and thus the whole supply chain is made more vulnerable to lost sales and/or backorders. The purpose of this paper is to recast the inventory model to be more relevant to current situations, where the penalty cost for a shortage occurrence at a downstream stage in a supply chain is continually transmitted to the upstream stages. The supplier, in this case, at the upstream of the supply chain is responsible for all the downstream shortages due to the chain reaction of its backlog. The current paper proposes a model in which the backorder cost per unit time is a linearly increasing function of shortage time, and it claims that the optimal policy for the supplier is setting the optimal shortage time per inventory cycle to minimize its total relevant cost in a JIT environment.     

Optimal Contract Design of Supplier-Led Outsourcing Based on Pontryagin Maximum Principle

This paper provides a supplier-led outsourcing model to maximize the supplier’s profits based on a principal-agent framework with both asymmetric cost information and uncertain market demand information described by continuous random variables. The salvage value of the unsold product is processing-cost dependent. By converting the proposed model, which is a dynamic optimization problem, to an optimal control problem, we obtain the analytical form of the optimal supplier outsourcing contract composed of the wholesale price and the transfer payment by applying Pontryagin’s maximum principle. It is shown that the optimal contract is directly related to the supplier’s beliefs about the manufacturer’s unit cost and the salvage value function. The Pontryagin’s maximum principle-based solution method serves as a powerful tool to support the decision making for the best sourcing strategy, and it provides analytical insights for outsourcing management. Finally, numerical examples are presented to illustrate the validness of the theoretical results.     

An inventory model where backordered demand ratio is exponentially decreasing with the waiting time

We analyze an inventory system with a mixture of backorders and lost sales, where the backordered demand rate is an exponential function of time the customers wait before receiving the item. Stockout costs (backorder cost and lost sales cost) include a fixed cost and a cost proportional to the length of the shortage period. A procedure for determining the optimal policy and the maximum inventory profit is presented. This work extends several inventory models of the existing literature.     

Call,put and bidirectional option contracts in agricultural supply chains with sales effort

This paper develops option contracts in a supplier-retailer agricultural supply chain where the market demand depends on sales effort. First, we examine a benchmark case of integrated supply chain with the loss rate. Second, we introduce three coordinating option contracts led by the supplier to reduce the retailer's risk, where the call option contract can reduce the shortage risk, the put option contract can reduce the inventory risk and the bidirectional option contract can reduce the bilateral risk. We find that both the optimal initial order quantity and the optimal option quantity increase with the sales effort and the option price will balance the influence of the loss rate on supply chain coordination. Furthermore, the bidirectional option price is the highest while its option quantity is the least, and the put option initial order quantity is the highest. Third, we also consider an option contract led by the retailer to reduce the supplier's wholesale risk. Among the above four option contracts, we find that the option quantity led by the retailer is the highest. Finally, the numerical examples present the impact of the parameters on the optimal decisions, and provide practical managerial insights to reduce the different risk in the agricultural supply chain.     

Inventory systems with stochastic demand and supply: Properties and approximations

We model a retailer whose supplier is subject to complete supply disruptions. We combine discrete-event uncertainty (disruptions) and continuous sources of uncertainty (stochastic demand or supply yield), which have different impacts on optimal inventory settings. This prevents optimal solutions from being found in closed form. We develop a closed-form approximate solution by focusing on a single stochastic period of demand or yield. We show how the familiar newsboy fractile is a critical trade-off in these systems, since the optimal base-stock policies balance inventory holding costs with the risk of shortage costs generated by a disruption.     

Integration of pricing and capacity allocation for perishable products

For years pricing and capacity allocation decisions in most revenue management models have been carried out independently. This article presents a comprehensive model to integrate these two decisions for perishable products. We assume that the supplier sells the same products to different micro-markets at distinct prices. Throughout the sales season, the supplier faces decisions as to which micro-markets or customer classes should be served and at what prices. We show that (i) at any time, a customer class is active (being served) if and only if the price offered is over a threshold level, but the optimal price may not be the highest one of the supplier’s choice; (ii) when the price decision is made in conjunction with inventory, it is similar to the procedure shown in pure pricing models, i.e., the optimal price comes from a subset of prices that forms a maximum increasing concave envelope; (iii) because of dynamic changes in the optimal prices, the nested-price structure does not necessarily hold in general and needs to be redefined; and (iv) the optimal pricing and capacity control policy is based on a sequence of threshold points that incorporate inventory, price and demand intensity. Numerical examples are provided.     

An EOQ model for deteriorating items under trade credits

In the classical inventory economic order quantity (or EOQ) model, it was assumed that the supplier is paid for the items immediately after the items are received. However, in practices, the supplier may simultaneously offer the customer: (1) a permissible delay in payments to attract new customers and increase sales, and (2) a cash discount to motivate faster payment and reduce credit expenses. In this paper, we provide the optimal policy for the customer to obtain its minimum cost when the supplier offers not only a permissible delay but also a cash discount. We first establish a proper model, and then characterize the optimal solution and provide an easy-to-use algorithm to find the optimal order quantity and replenishment time. Furthermore, we also compare the optimal order quantity under supplier credits to the classical economic order quantity. Finally, several numerical examples are given to illustrate the theoretical results.     

Note on inventory model with a mixture of back orders and lost sales

Competitiveness is an important means of determining whether a company will prosper. Business organizations compete with one another in a variety of ways. Among these competitive methods are time and cost factors. The purpose of this paper is to examine the inventory models presented by Padmanabhan and Vrat [International Journal of Systems Sciences 21 (1990) 1721] with a mixture of back orders and lost sales. We develop the criterion for the optimal solution for the total cost function. If the criterion is not satisfied, this model will degenerate into one cycle inventory model with a finite inventory period. This implies an extension of shortage period as long as possible to produce lower cost. However, we know that time is another important factor in company competitiveness. Customers will not indefinitely wait for back orders. A tradeoff will be made between the two most important factors; time and cost. The minimum total cost is evaluated under the diversity cycle time and illustrations are applied to explain the calculation process. This work provides a reference for decision-makers.     

顾客策略行为下基于联合促销努力的风险规避供应链协调模型

本文在考虑顾客策略行为情形下,利用条件风险度量准则建立了带有联合促销努力供应链协调模型,研究了风险规避对销售商和供应商决策行为的影响,得到了如下研究结论:(1)集中决策情形,价格承诺策略既可以激励供应商提高生产量,还能够有效降低顾客策略行为对其产生的负面影响。(2)分散决策情形,销售商风险规避度增大,销售商的订购量将增加,供应商的销售努力也将增加;供应商风险规避度增大,销售商的订购量将减小,供应商的销售努力也将减小;无论供应商和销售商的风险规避如何变化,销售商的销售努力不变。(3)利用回购和成本分担组成的混合契约可以实现供应链完美协调。     

Designing a new computational approach of partial backlogging on the economic production quantity model for deteriorating items with non-linear holding cost under inflationary conditions

This paper discusses the production inventory model over an infinite time horizon. Here we consider demand as a function of stock and time. Deterioration is a function of time and time-varying production. Our objective is to minimize the total cost which is a function of set up cost, holding cost, shortage cost, and opportunity cost due to lost sales. The traditional costs such as purchasing cost, shortage cost and opportunity cost due to lost sales are kept constant. We consider holding cost to be a non-linear function of time. Shortages are allowed and are partially backlogged. Here, time durations are the decision variables. Numerical examples are given to illustrate the model.     

Dynamic pricing inventory control under fixed cost and lost sales

This paper studies a periodic review pricing and inventory replenishment problem which encounters stochastic demands in multiple periods. In many inventory control problems, the unsatisfied demand is traditionally assumed to be backlogged but in this paper is assumed to be lost. In many practical problems, a consumer who could not buy what he/she wants in one store is not willing to wait until that store restocks it but tries to buy alternatives in other stores. Also, in this paper, the random variable for the demand function is assumed to be general, which means that any probability function for the random variable can be applied to our result. Cost terms consist of the holding cost by the leftover, the shortage cost by lost sales, and the strictly positive fixed ordering cost. The objective of this paper is to dynamically and simultaneously decide the optimal selling price and replenishment in each period by maximizing the expected profit over the finite selling horizon. We show that, under the general assumption on the random variable for the demand, the objective function is K$K$-concave, an (s,S)$(s\text{,}S)$ policy is optimal for the replenishment and the optimal price is determined based on the inventory level after the replenishment in each period.     

A deteriorating inventory model with time-varying demand and shortage-dependent partial backlogging

Recently, Chu et al. [P. Chu, K.L. Yang, S.K. Liang, T. Niu, Note on inventory model with a mixture of back orders and lost sales, European Journal of Operational Research 159 (2004) 470–475] presented the necessary condition of the existence and uniqueness of the optimal solution of Padmanabhan and Vrat [G. Padmanabhan, P. Vrat, Inventory model with a mixture of back orders and lost sales, International Journal of Systems Science 21 (1990) 1721–1726]. However, they included neither the purchase cost nor the cost of lost sales into the total cost. In this paper, we complement the shortcoming of their model by adding not only the cost of lost sales but also the non-constant purchase cost, and then extend their model from a constant demand function to any log-concave demand function. We also provide a simple solution procedure to find the optimal replenishment schedule. Further, we use a couple of numerical examples to illustrate the results and conclude with suggestions for future research.     

A stochastic periodic review integrated inventory model involving defective items, backorder price discount, and variable lead time

The purpose of this article is to investigate a stochastic integrated supplier-retailer inventory problem. The model analyzed in this article explores the problem of the protection interval, the backorder price discount, the lead time, and the numbers of shipments from the supplier to the retailer in one production run as control variables to widen applications for an integrated periodic review inventory model. We consider the situation in which the supplier and the retailer establish a long-term strategic partnership and contract to jointly determine the best strategy. We assume that the protection interval demand follows a normal distribution. Our objective is to determine the optimal review period, the optimal backorder price discount, the optimal lead time, and the optimal number of shipments from the supplier to the retailer in one production run, so that the joint expected annual total cost incurred has the minimum value. Furthermore, an algorithm of finding the optimal solution is developed. Also, the sensitivity analysis included and a numerical example is given to illustrate the results of the proposed model.     

Inventory and sales effort management under unobservable lost sales

A retailer needs to make decisions regarding how much to order and how much sales effort to exert in an environment with uncertain demand. One intrinsic complexity in a typical retail environment is caused by the fact that the retailer can obtain information about demand only based on sales, as demand itself is unobservable. Taking a Bayesian approach, Lariviere and Porteus (1999) show that in such a setting a retailer should stock more to increase the probability of an exact demand observation. In this article, we extend their work by allowing the retailer to control both the stocking quantity and sales effort, which can be used to affect demand. We show that their insights with respect to information stalking carry over to this setting. In addition, our model allows gaining a better understanding of optimal sales effort strategies. We find that demand management has a dual role in supporting information gathering: while at the beginning of a product life cycle it is optimal to support learning effects by sharply reducing sales effort, at later stages of the product life cycle an aggressive strategy of increased promotional activities can be used to harvest the information gathered in earlier periods.     

An optimal replenishment policy for an EOQ model with partial backlogging

We study an inventory system where demand on the stockout period is partially backlogged. The backlogged demand ratio is a mixture of two exponential functions. The shortage cost has two significant costs: the unit backorder cost (which includes a fixed cost and a cost proportional to the length of time for which the backorder exists) and the cost of lost sales. A general procedure to determine the optimal policy and the minimum inventory cost for all the parameter values is developed. This model generalizes several inventory systems analyzed by different authors. Numerical examples are used to illustrate the theoretical results.