Newsvendor with multiple options of expediting

We consider a manufacturer facing single period inventory planning problem with uncertain demand and multiple options of expediting. The demand comes at a certain time in the future. The manufacturer may order the product in advance with a relatively low cost. She can order additional amount by expediting after the demand is realized. There are a number of expediting options, each of which corresponds to a certain delivery lead time and a unit procurement price. The unit procurement price is decreasing over delivery lead time. The selling price is also decreasing over time. In this paper, we assume that the manufacturer must deliver all products to the customer in a single shipment. The problem can be formulated as a profit maximization problem. We develop structural properties and show how the optimal solution can be identified efficiently. In addition, we compare our model with the classical newsvendor model and obtain a number of managerial insights.     

Optimal acquisition and production policy in a hybrid manufacturing/remanufacturing system with core acquisition at different quality levels

We study the acquisition and production planning problem for a hybrid manufacturing/remanufacturing system with core acquisition at two (high and low) quality conditions. We model the problem as a stochastic dynamic programming, derive the optimal dynamic acquisition pricing and production policy, and analyze the influences of system parameters on the acquisition prices and production quantities. The production cost differences among remanufacturing high- and low-quality cores and manufacturing new products are found to be critical for the optimal production and acquisition pricing policy: the acquisition price of high-quality cores is increasing in manufacturing and remanufacturing cost differences, while the acquisition price of low-quality cores is decreasing in the remanufacturing cost difference between high- and low-quality cores and increasing in manufacturing and remanufacturing cost differences; the optimal remanufacturing/manufacturing policy follows a base-on-stock pattern, which is characterized by some crucial parameters dependent on these cost differences.     

部分延迟订购的易变质品联合定价与生产策略

构建了一个需求同时依赖于销售价格和库存水平,生产率和变质率均为常数,允许缺货且缺货量部分延迟订购的易变质品联合定价与生产控制模型。首先证明了在销售价格给定的情况下,系统的总利润函数是关于生产计划的严格凹函数,平均利润函数是严格的伪凹函数,即存在唯一的最优解,并给出其充分条件。接着给出问题的一个数值求解算法。最后通过算例,展示了模型及相关算法的应用,并对相关参数进行了灵敏度分析,结果显示:当产品的生产成本、缺货成本和机会成本增加时,系统的平均利润将下降;生产成本和延迟订购阻力系数对最优定价和生产策略以及平均利润的影响较大。     

需求不确定的强势零售商的闭环供应链决策

建立了需求不确定下两个竞争的生产商和一个强势零售商组成的具有产品再制造的闭环供应链模型.利用逆向归纳法对不同废旧品回收渠道下的模型进行分析,然后通过算例分析了不同模型的回收成本和新增回收率对零售价格、回收模式决策、供应链系统及成员期望利润的影响.结果表明:回收成本的增加导致生产商和系统的期望利润降低,零售商领头下只有在零售商负责回收的模式中,零售商的期望利润才是增加的;新增回收率的增加,可降低产品的零售价,增加供应链成员的期望利润,继而提高整个供应链系统的利润.     

Dynamic decision-making for an inventory system with time-varying demand

This article considers the problem of dynamic decision-making for time-varying demand products under trade credit. The article adopts a price, warranty length and time-dependent demand function to model the finite time horizon inventory. The objective of this study is to determine the optimal periodic selling price, warranty length and ordering quantity so that the total profit is maximized. We discuss the optimization properties and develop solution procedures based on dynamic programming techniques for solving the problem described. The numerical analyses show that dynamic decision-making is superior to fixed decision-making and an appropriate warranty policy can benefit the company. This study also discusses the effects of interest earned, interest charged and credit period on company's decisions and profits.     

Pricing used products for remanufacturing

Remanufacturing is one of recovery options for used products. As remanufacturing requires a continuous supply of used products, the economic incentive is required to attract customers to return their used products (called cores) and the problem of pricing a core becomes an important issue. Such a pricing problem is analogous to pricing an option, which can be used to sell the remanufactured cores (called core products). As sales price of core products follows a geometric Brownian motion, we propose a model here to evaluate the acquisition price of cores. This model links core acquisition price with the sale price of core product but assumes other costs such as logistics and remanufacturing to be deterministic. We have presented a numerical example to show its applicability. Since the model proposed here is generic, it is believed that the proposed model can be used in setting the core prices in many situations.     

Optimisation of integrated reverse logistics networks with different product recovery routes

The awareness of importance of product recovery has grown swiftly in the past few decades. This paper focuses on a problem of inventory control and production planning optimisation of a generic type of an integrated Reverse Logistics (RL) network which consists of a traditional forward production route, two alternative recovery routes, including repair and remanufacturing and a disposal route. It is assumed that demand and return quantities are uncertain. A quality level is assigned to each of the returned products. Due to uncertainty in the return quantity, quantity of returned products of a certain quality level is uncertain too. The uncertainties are modelled using fuzzy trapezoidal numbers. Quality thresholds are used to segregate the returned products into repair, remanufacturing or disposal routes. A two phase fuzzy mixed integer optimisation algorithm is developed to provide a solution to the inventory control and production planning problem. In Phase 1, uncertainties in quantity of product returns and quality of returns are considered to calculate the quantities to be sent to different recovery routes. These outputs are inputs into Phase 2 which generates decisions on component procurement, production, repair and disassembly. Finally, numerical experiments and sensitivity analysis are carried out to better understand the effects of quality of returns and RL network parameters on the network performance. These parameters include quantity of returned products, unit repair costs, unit production cost, setup costs and unit disposal cost.     

Optimal pricing,production, and inventory for deteriorating items under demand uncertainty: The finite horizon case

This paper aims to investigate the joint dynamic pricing and production decisions of deteriorating items with uncertain demand over a finite selling season, where the demand is price sensitive and the potential demand is characterized by a stochastic process. The stocks deteriorate physically at a constant fraction of the on-hand inventory. A joint dynamic pricing and production problem to maximize the total expected profit is modeled as a stochastic optimal control problem. We derive the closed-form solutions, which are in time-dependent linear feedback form of the inventory level when it is either positive or negative. It is shown that the manufacturer always benefits from a reduction in the volatility of potential market demand. In addition, to highlight the effectiveness of the joint dynamic strategy, we also consider the case of optimal production with a static price. A numerical example is presented to illustrate the validity of the optimal control policy, and sensitivity analysis on major parameters is performed to provide more managerial insights into deteriorating items.     

Dynamic pricing of inventory with cancellation demand

When an inventory item has such a limited selling period that only a single supply order can be placed to satisfy future demand, a decision-maker must determine the quantity of the order to meet future demand and how to price this stock. Although this problem has received considerable attention, related investigations typically view the demand and selling price as exogenous parameters and assume that customers cannot cancel an order or return the product after purchasing the item. Pricing is, however, an important pervasive marketing vehicle that affects demand, and customers indeed cancel or return their orders after placing them. The newsboy problem is extended here so that demand is price-dependent and customers may cancel their orders. This paper seeks to develop decision rules to maximize the total expected profit over a given planning period. Analysis results demonstrate the feasibility of applying the order-up-to structure to yield the order quantity.     

Construction of a model towards EOQ and pricing strategy for gradually obsolescent products

Due to the rapid advance of technology, manufacturers’ marketing models and quickly changing consumer tastes, products such as apparel, clothing accessories and consumer electronics are likely to face the problem of short product life cycles. This study deals with the problem of determining order quantity and multi-discount selling prices for these types of gradually obsolescent products, in which two novel proposals are presented as follows: (1) without considering any exogenous factors that could affect demand, we develop a time-dependent demand model that appropriately portrays an integrated demand behavior associated with the characteristic of obsolescence; (2) we then treat the selling price as an exogenous factor influencing demand and, referring to the linear demand D = α − βp, the effect that “the increase of demand due to price change is linearly correlated with the difference between two consecutive selling prices” is incorporated, so as to make the demand model be a function of both time and selling price. Afterwards, optimization models are hereby formulated to predetermine pricing strategy with a limited number of price changes by maximizing retailer’s profit. As a result, numerical examples illustrate that the multi-discount model indeed provides higher total profit than a single discount one. This is presented along with the result analysis conducted to gain some managerial insights.     

A robust optimization model for dynamic market with uncertain production cost

This article presents a robust optimization formulation for dealing with production cost uncertainty in an oligopolistic market scenario. It is not uncommon that players in the market face an equilibrium selling price but uncertain production costs. We show that, based on a nominal problem, the robust optimization formulation can be derived as a variational inequality with control and state variables. This convenient approach may be applied for computing optimal solutions efficiently, which help manufacturers dramatically and rapidly reform production and distribution schedules such that they can compete in the market successfully.     

A robust optimization model for multi-product two-stage capacitated production planning under uncertainty

Production planning (PP) is one of the most important issues carried out in manufacturing environments which seeks efficient planning, scheduling and coordination of all production activities that optimizes the company’s objectives. In this paper, we studied a two-stage real world capacitated production system with lead time and setup decisions in which some parameters such as production costs and customer demand are uncertain. A robust optimization model is developed to formulate the problem in which minimization of the total costs including the setup costs, production costs, labor costs, inventory costs, and workforce changing costs is considered as performance measure. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. A mixed-integer programming (MIP) model is developed to formulate the related robust production planning problem. In fact the robust proposed model is presented to generate an initial robust schedule. The performance of this schedule could be improved against of any possible occurrences of uncertain parameters. A case from an Iran refrigerator factory is studied and the characteristics of factory and its products are discussed. The computational results display the robustness and effectiveness of the model and highlight the importance of using robust optimization approach in generating more robust production plans in the uncertain environments. The tradeoff between solution robustness and model robustness is also analyzed.     

Fuzzy profit measures for a fuzzy economic order quantity model

Changing economic conditions make the selling price and demand quantity more and more uncertain in the market. The conventional inventory models determine the selling price and order quantity for a retailer’s maximal profit with exactly known parameters. This paper develops a solution method to derive the fuzzy profit of the inventory model when the demand quantity and unit cost are fuzzy numbers. Since the parameters contained in the inventory model are fuzzy, the profit value calculated from the model should be fuzzy as well. Based on the extension principle, the fuzzy inventory problem is transformed into a pair of two-level mathematical programs to derive the upper bound and lower bound of the fuzzy profit at possibility level α. According to the duality theorem of geometric programming, the pair of two-level mathematical programs is transformed into a pair of conventional geometric programs to solve. By enumerating different α values, the upper bound and lower bound of the fuzzy profit are collected to approximate the membership function. Since the profit of the inventory problem is expressed by the membership function rather than by a crisp value, more information is provided for making decisions.     

Dynamic pricing of remanufacturable products under demand substitution: a product life cycle model

We consider a manufacturer who sells both the new and remanufactured versions of a product over its life cycle. The manufacturer’s profit depends crucially on her ability to synchronize product returns with the sales of the remanufactured product. This gives rise to a challenging dynamic optimization problem where the size of both the market and the user pool are dynamic and their current values depend on the entire history. We provide an analytical characterization of the manufacturer’s optimal pricing, production, and inventory policies which lead to a practical threshold policy with a small optimality gap. In addition, our analysis offers a number of interesting insights. First, the timing of remanufacturing activity and its co-occurrence with new product manufacturing critically depends on remanufacturing cost benefits, attractiveness of the remanufactured product and product return rate. Second, there is a small upward jump in the price of the new product when remanufacturing is introduced. Third, the manufacturer keeps the new product longer on the market as the cost of remanufacturing decreases. Fourth, partially satisfying demand for the remanufactured item is never optimal, i.e., it is satisfied either fully or not at all. Finally, user pool and inventory of returned products are substitutes in ensuring the supply for future remanufacturing.     

基于回收风险的闭环供应链差异定价决策研究

随着资源的匮乏和环境污染的加剧,越来越多的企业和消费者开始关注废旧产品的回收再制造。针对制造商唯一寡头垄断市场竞争结构,引入回收风险,分别对制造商(OEM)自行回收废旧产品的闭环供应链、第三方回收商回收废旧产品的闭环供应链建立数学模型,分析给出各企业的最优差异定价规则,并从经济学意义上得到相关管理启示;数值实验的结果则进一步验证回购价格、回收风险、价格竞争强度对最优解的影响。研究结果表明:(1)闭环供应链结构会影响再制品价格及废旧产品的回收价格,但对OEM新品定价无影响。(2)回收风险的变化对价格决策的影响取决于闭环供应链的结构特征。当回收风险较低时,在激发消费者对再制品需求、促使消费者返回废旧产品、提升闭环供应链整体效率等方面,OEM自行回收模式优于第三方回收商回收模式;而当回收风险较高时,则第三方回收商回收模式优于OEM自行回收模式。(3)回收风险的降低使得闭环供应链总利润呈现出增长的趋势,进而进一步体现到再制造的经济价值。(4)OEM自行回收废旧产品需考虑到新品与再制品间的价格竞争强度,当价格竞争强度较弱时,OEM自行回收废旧产品可为OEM带来更多的利润;新品与再制品间的价格竞争也有利于再制品需求的提升。     

Production planning for hybrid remanufacturing and manufacturing system with component recovery

In this paper, we address component recovery under the condition of limited resources from the OEM's (Original Equipment Manufacturer's) standpoint. We develop a linear programming model for a hybrid remanufacturing and manufacturing system for production planning problems with deterministic returns. In this paper, a data set from an OEM that both remanufactures and manufactures the products is used to demonstrate the performance of the proposed model. Subsequently, an analysis of the impact of the remanufactured product’s price and the quantity of returns on revenue and total cost will be discussed. We have found that uncertain factors of manufacturing influence the profit and uncertain factors of remanufacturing influence the production planning, such as the rate of the yield on component remanufacturing and the quantity of returns.     

Coordination mechanism for the supply chain with leadtime consideration and price-dependent demand

We study a coordination contract for a supplier–retailer channel producing and selling a fashionable product exhibiting a stochastic price-dependent demand. The product’s selling season is short, and the supply chain faces great demand uncertainty. We consider a scenario where the supplier reserves production capacity for the retailer in advance, and permits the retailer to place an order not exceeding the reserved capacity after a demand information update during a leadtime. We formulate a two-stage optimization problem in which the supplier decides the amount of capacity reservation in the first stage, and the retailer determines the order quantity and the retail price after observing the demand information in the second stage. We propose a three-parameter risk and profit sharing contract that coordinates the supply chain. The proposed contract permits any agreed-upon division of the supply-chain profit between the channel members.     

Periodic pricing and replenishment policy for continuously decaying inventory with multivariate demand

This paper deals with the joint decisions on pricing and replenishment schedule for a periodic review inventory system in which a replenishment order may be placed at the beginning of some or all of the periods. We consider a single product which is subject to continuous decay and a demand which is a function of price and time, without backlogging over a finite planning horizon. The proposed scheme may adjust periodically the selling price upward or downward that makes the pricing policy more responsive to structure changes in supply or demand. The problem is formulated as a dynamic programming model and solved by numerical search techniques. An extensive numerical study is conducted to attend qualitative insights into the structures of the proposed policy and its sensitivity with respect to major parameters. The numerical result shows that the solution generated by the periodic policy outperforms that by the fixed pricing policy in maximizing discount profit.     

Production planning and pricing policy in a make-to-stock system with uncertain demand subject to machine breakdowns

We consider a make-to-stock system served by an unreliable machine that produces one type of product, which is sold to customers at one of two possible prices depending on the inventory level at the time when a customer arrives (i.e., the decision point). The system manager must determine the production level and selling price at each decision point. We first show that the optimal production and pricing policy is a threshold control, which is characterized by three threshold parameters under both the long-run discounted profit and long-run average profit criteria. We then establish the structural relationships among the three threshold parameters that production is off when inventory is above the threshold, and that the optimal selling price should be low when inventory is above the threshold under the scenario where the machine is down or up. Finally we provide some numerical examples to illustrate the analytical results and gain additional insights.     

技术许可下信息分享和政府补贴对闭环供应链的影响分析——基于经销商再制造模式

研究了信息分享对制造商许可经销商从事再制造模式下闭环供应链的影响。分别建立了无信息分享和信息分享下经销商再制造和制造商再制造两种模式下的闭环供应链模型并分析了政府补贴对废旧产品回收量和渠道成员决策的影响。研究发现,当经销商对制造商进行信息分享时,经销商的利润减少,而制造商的利润增加。渠道领导者制造商总是能从再制造活动中抽取利润,在经销商再制造模式下,制造商通过收取许可费分享再制造的利润;在制造商再制造模式下,制造商设定适当的批发价格及回收价格协调正向流和逆向流,从而实现利润最大化。同时表明了政府补贴的刺激会显著地提高废旧产品的回收量。