可替代产品库存模型的研究

市场上,很多产品之间可相互替代,商家为了获得的更多的利润,经常会用一种产品替代另一种产品.不仅如此.某种产品缺货时,也可以重新进货以满足顾客的需求.我们从销售商的角度,讨论这两个因素对库存策略的影响,建立了这类问题有两个产品的单周期的利润最大化模型,证明了目标函数是凹的和子模的,从而问题的解是存在的,给出了最优订货量(原始库存)的必要条件,讨论了各参数对库存的影响.通过比较,证明了商家采取替代策略和允许再订货可以提高利润并且可减少库存总量.     

Analytical and managerial implications of integrating product substitutability in the joint pricing and procurement problem

This paper studies the analytical and managerial implications of product substitutability on the joint pricing and procurement decisions. We consider a single-period model with two products: an existing product and an improved new product that can substitute the demand for the existing product in case of a shortage. Demand for each product follows a general distribution with an expected value that is a linear function of the price of the new product. While the price of the existing product is determined by the market, it is necessary to determine the new product’s price and the procurement quantities of both products so as to maximize the profits. We analytically show that the expected profit function is unimodal and in the existence of substitution: the expected total profit is higher; the optimal price and the safety stock of the new product are higher; and the optimal safety stock of the existing product is less. Using these properties an efficient algorithm is developed. We also provide a numerical analysis to demonstrate that considering substitution in advance could increase the profitability by 58% and the new product price by 5% while decreasing the total procurement quantity by 15%.     

Incorporating one-way substitution policy into the newsboy problem with imprecise customer demand

This paper presents an approach for solving an inventory model for single-period products with maximizing its expected profit in a fuzzy environment, in which the retailer has the opportunity for substitution. Though various structures of substitution arise in real life, in this study we consider the fuzzy model for two-item with one-way substitution policy. This one-way substitutability is reasonable when the products can be stored according to certain attribute levels such as quality, brand or package size. Again, to describe uncertainty usually probability density functions are being used. However, there are many situations in real world that utilize knowledge-based information to describe the uncertainty. The objective of this study is to provide an analysis of single-period inventory model in a fuzzy environment that enables us to compute the expected resultant profit under substitution. An efficient numerical search procedure is provided to identify the optimal order quantities, in which the utilization of imprecise demand and the use of one-way substitution policy increase the average expected profit. The benefit of product substitution is illustrated through numerical example.     

Bundling retail products: Models and analysis

We consider the impact of bundling products on retail merchandising. We consider two broad classes of retail products: basic and fashion. For these product classes, we develop models to calculate the optimal bundle prices, order quantities, and profits under bundling. We use this analysis to establish conditions and insights under which bundling is profitable. Our analysis confirms that bundling profitability depends on individual product demands, bundling costs, and the nature of the relationship between the demands of the products to be bundled. We also provide detailed numerical examples.     

可替代产品库存模型的研究

市场上，很多产品之间可相互替代，某种产品缺货时，可用另一种产品替代，也可以重新进货以满足顾客的需求。我们的目的是：从销售商的角度，讨论这两个因素对库存策略的影响。我们建立了这类问题有两个产品的单调期的利润最大化模型。证明了问题的解的存在性，给出了目标函数是凹函数和子模函数的充分条件，讨论了求解的方法和各参数对库存的影响。通过对几种特殊情况的讨论和比较，证明了替代和再订货可以提高利润并且可减少库存总量。     

Ordering and pricing decisions in a two-echelon supply chain with asymmetric demand information

This article examines coordinated decisions in a decentralized supply chain that consists of one supplier and one retailer, and faces random demand of a single product with a short life cycle. We consider a setting where the retailer has accurate demand information while the supplier does not. Such a problem with asymmetric demand information can be viewed as an extension of the newsboy problem in which both the supplier and the retailer possess the same demand information. Combining the mechanism of sharing demand information and that of quantity discount and return policy enables us to develop three coordinated models in contrast with the basic and uncoordinated model. We are able to show the ordinal relationship among the retailer’s optimal order quantities in these four models under a general form of random demand, and compare the supply chain profits and conduct sensitivity analysis analytically in four models under uniform random demand. We also provide numerical results under normal random demand that bear a resemblance to those under uniform random demand.     

Single-period Two-product Inventory Model with Reorder and Substitution

In market, excess demands for many products can be met by reorder even during one period, and retailers usually adopt substitution strategy for more benefit. Under the retailer's substitution strategy and permission of reorder, we develop the profits maximization model for the two-substitutable-product inventory problem with stochastic demands and proportional costs and revenues. We show that the objective function is concave and submodular, and therefore the optimal policy exists. We present the optimal conditions for order quantity and provide some properties of the optimal order quantities. Comparing our model with Netessine and Rudi's, we prove that reorder and adoption of the substitution strategy can raise the general profits and adjust down the general stock level.     

Joint replenishment model with substitution

When products are coupled to the same cycle, the joint replenishment model (JRM) is used to determine optimal inventory levels, where the amount to order (for each item) is designed to minimize the joint holding and ordering costs based on a given demand. JRM studies assume that there is no substitution between items. However, this assumption is unrealistic in some settings where substitution cannot be ignored. This paper combines the separate works on substitution and joint replenishment and proposes a solution procedure for solving the joint replenishment model with substitution (JRMS) for two products within the framework of the classical economic order quantity model. We determine the optimal order quantities for each product taking into consideration substitution between them so that demand is partially met and the total cost associated with the delivery, holding, and shortage of the products is minimized. We also provide an extensive scenario analysis and draw insights. In particular, we shed some light on the role of substitution in reducing the fixed cost. We show that JRMS can result in substantial cost savings compared to the ordinary JRM.     

Conditions that cause risk pooling to increase inventory

We say product A is a partial substitute for product B if a fraction of the customers who prefer B are willing to accept A when B is out of stock. When demand is uncertain, it is intuitive and true that a larger “willing to substitute” fraction implies larger expected profits. A higher “willing to substitute” fraction allows one to pool the risk of individual products. It may also be intuitive that a larger “willing to substitute” fraction might result in lower optimal total inventory. For the full substitution structure, several researchers have shown that for certain distributions such as the exponential, this latter intuition is not true. We show that this full substitution anomaly can occur with any right skewed demand distribution. We assume i.i.d. demand distributions unless we indicate otherwise. We also show that the anomaly can occur for a number of realistic situations of partial substitution with commonly used demand distributions such as Normal, exponential, Poisson, and uniform. We also demonstrate the anomaly for more than one period, with backlogging, lost sales, more than two products, and with setup costs.     

基于制造商资金有约束的替代产品的最优生产决策

考虑一个单周期的生产决策模型,在该模型中有一个制造商生产两种可替代的产品.面对随机的市场需求,制造商要在需求到来之前制定出两种产品的生产决策来最大化自己的期望利润.在制造商的资金有、无约束两种情形下,证明了制造商的收益函数的期望是关于两种产品生产数量的凹函数,探讨了资金的约束以及产品的替代给制造商的生产决策所带来的影响,给出了最优生产数量的若干性质.另外,针对需求分布为均匀分布的特殊情形给出了制造商最优生产决策的简单表达形式.     

A two-echelon supply chain of a returnable product with fuzzy demand

This study investigates the effects of the manufacturer’s refund on retailer’s unsold products for the two-echelon decentralized and centralized supply chains of a short life and returnable product with trapezoidal fuzzy demand, in which retailer returns the unsold and the customer’s unsatisfactory products to the manufacturer. For each returnable chain, we obtain the closed-form solution of order quantity to maximize the total expected profit of the supply chain, and confirm that demand fuzziness does indeed affect the order quantity and the members’ expected profits. We provide a number of managerial insights by comparing both chains and show that each chain is more advantageous to the members depending on certain condition. Our models are appropriate for a supply chain with a returnable product that lacks information about the demand.     

Assortment planning in fashion retailing: methodology,application and analysis

Assortment planning is the process conducted by the retailer to determine the number and types of products in a line. Key questions that arise in this process include choosing the inventory depth and variety breadth, and the mix between basic and fashion merchandise of the assortment to maximize expected profits. We describe a method for resolving these questions. Using demand forecasts derived from historical sales patterns, we use a nonlinear integer programming model to make the assortment choice. Efficient heuristics are developed to solve this problem. We applied our method at a large catalog retailer specializing in women’s apparel. We compared our method to the existing rules used by this retailer and found that it could choose the assortment in a manner that reduces markdowns due to excessive inventory and lost margins due to stockouts by enough to increase profits by at least 40%. Insights are developed to better understand why products are included in an assortment and the implications of this choice on the realized profit. We extend our model to include shelf space constraints and the effect of assortment choice on product demand.     

Heuristics for the multi-depot petrol station replenishment problem with time windows

In the multi-depot petrol station replenishment problem with time windows (MPSRPTW), the delivery of petroleum products stored in a number of different petroleum depots to a set of petrol distribution stations has to be optimized. Each depot has its own fleet of heterogeneous and compartmented tank trucks. Stations specify their demand by indicating the minimum and maximum quantities to be delivered for each ordered product and require the delivery within a predetermined time window. Several inter-related decisions must be made simultaneously in order to solve the problem. For this problem, the set of feasible routes to deliver all the demands, the departure depot for each route, the quantities of each product to be delivered, the assignment of these routes to trucks, the time schedule for each trip, and the loading of the ordered products to different tanks of the trucks used need to be determined. In this paper, we propose a mathematical model that selects, among a set of feasible trips, the subset that allows the delivery of all the demands while maximizing the overall daily net revenue. If this model is provided with all possible feasible trips, it determines the optimal solution for the corresponding MPSRPTW. However, since the number of such trips is often huge, we developed a procedure to generate a restricted set of promising feasible trips. Using this restricted set, the model produces a good but not necessarily optimal solution. Thus the proposed solution process can be seen as a heuristic. We report the results of the extensive numerical tests carried out to assess the performance of the proposed heuristic. In addition, we show that, for the special case of only one depot, the proposed heuristic outperforms a previously published solution method.     

On the assortment optimization with endogenized market size

In this paper, we consider the joint effects of product substitution and market size endogenization. Under the substitution effects, a product’s demand may be cannibalized by other substitutable products; while the market size, measured by the number of customers who are interested in the products from the same category, may be largely influenced by the product offer set. We establish the computational complexity for the assortment problem under the joint effects, and develop a fully polynomial-time approximation scheme (FPTAS).     

Deterministic hierarchical substitution inventory models

In this paper, we consider a deterministic nested substitution problem where there are multiple products which can be substituted one for the other, if necessary, at a certain cost. We consider the case when there are n products, and product j can substitute products j + 1,…,n at certain costs. The trade-off is the cost of storing products (for example, customised products) at a higher inventory holding stage versus the cost of transferring downwards from a lower inventory holding cost (generic product) stage. The standard approach to solving the problem yields an intractable formulation, but by reformulating the problem to determine the optimal run-out times, we are able to determine the optimal order and substitution quantities. Numerical examples showing the effect of various system parameters on the optimal order and substitution policy are also presented.     

可替代产品库存模型的研究

以零售商的角度,讨论了在允许进货的情况下可替代产品的库存问题,建立了这类问题利润最大化的库存模型,讨论了各参数对利润和库存的影响.然后证明了问题的解是存在的,利润函数是子模的,并给出了最优解的一阶必要性条件,同时探讨了目标函数的凹性问题.通过理论分析和数值试验证明了在一定条件下替代和重新进货都能提高利润,并能降低总的库存水平.     

Component rationing for available-to-promise scheduling in configure-to-order systems

We address the problem of rationing common components among multiple products in a configure-to-order system with order configuration uncertainty. The objective of this problem is to maximize expected revenue by implementing a threshold rationing policy. Under this policy, a product is available to promise if fulfilling the order for the product will not cause the inventory of any one of its required components to fall below the component’s threshold level for that product. The problem is modeled as a two-stage stochastic integer program and solved using the sample average approximation approach. A heuristic is developed to generate good feasible solutions and lower bound estimates. Using industry data, we examine the benefit of component rationing as compared to a First-Come-First-Served policy and show that this benefit is correlated to the average revenue per product and the variability in the revenue across products whose components are constrained.     

Time-dependent and independent control rules for coordinated production and pricing under demand uncertainty and finite planning horizons

We address the effect of uncertainty on a manufacturer’s dynamic production and pricing decisions over a finite planning horizon. The demand for products, which depends on their price, is characterized by two stochastic processes: potential demand and customer price sensitivity. An optimal policy for coordinating production and pricing is a time-dependent feedback rule with respect to the state of the manufacturer’s inventories. We show that when the volatility of customer sensitivity to the product price is negligible, the optimal policy can be obtained analytically. Moreover, our simulations demonstrate that the volatility of stochastic customer price sensitivity does not have a strong effect on the manufacturer’s expected profit. Therefore, the solution derived for the case of customer price sensitivity with zero volatility can serve as a good approximation heuristic for the optimal policy if the true volatility of customer price sensitivity is within 40 % of its mean and the volatility of potential demand is within 25 % of its mean. Moreover, under these conditions, a simplified, time-independent control rule deteriorates expected profits by only 1.5 %.     

A multi-period ordering and clearance pricing model considering the competition between new and out-of-season products

The joint management of pricing and inventory for perishable products has become an important problem for retailers. This paper investigates a multi-period ordering and clearance pricing model under consideration of the competition between new and out-of-season products. In each period, the ordering quantity of the new product and the clearance price of the out-of-season product are determined as decision variables before the demand is realized, and the unsold new product becomes the out-of-season one of the next period. We establish a finite-horizon Markov decision process model to formulate this problem and analyze its properties. A traditional dynamic program (DP) approach with two-dimensional search is provided. In addition, a myopic policy is derived in which only the profit of the current period is considered. Finally, we apply genetic algorithm (GA) to this problem and design a GA-based heuristic approach, showing by comparison among different algorithms that the GA-based heuristic approach is more performance sound than the myopic policy and much less time consuming than the DP approach.     

Production-inventory control policy under warm/cold state-dependent fixed costs and stochastic demand: partial characterization and heuristics

The motivation for our study comes from some production and inventory systems in which ordering/producing quantities that exceed certain thresholds in a given period might eliminate some setup activities in the next period. Many examples of such systems have been discussed in prior research but the analysis has been limited to production settings under deterministic demand. In this paper, we consider a periodic-review production-inventory model under stochastic demand and incorporate the following fixed-cost structure into our analysis. When the order quantity in a given period exceeds a specified threshold value, the system is assumed to be in a “warm” state and no fixed cost is incurred in the next period regardless of the order quantity; otherwise the system state is considered “cold” and a positive fixed cost is required to place an order. Assuming that the unsatisfied demand is lost, we develop a dynamic programming formulation of the problem and utilize the concepts of quasi-K-convexity and non-K-decreasing to show some structural results on the optimal cost-to-go functions. This analysis enables us to derive a partial characterization of the optimal policy under the assumption that the demands follow a Pólya or uniform distribution. The optimal policy is defined over multiple decision regions for each system state. We develop heuristic policies that are aimed to address the partially characterized decisions, simplify the ordering policy, and save computational efforts in implementation. The numerical experiments conducted on a large set of test instances including uniform, normal and Poisson demand distributions show that a heuristic policy that is inspired by the optimal policy is able to find the optimal solution in almost all instances, and that a so-called generalized base-stock policy provides quite satisfactory results under reasonable computational efforts. We use our numerical examples to generate insights on the impact of problem parameters. Finally, we extend our analysis into the infinite horizon setting and show that the structure of the optimal policy remains similar.