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1.
本文研究服务水平约束下的动态定价与库存管理问题。企业在有限期内销售某种产品,产品的需求为随机需求,且期望需求依赖于产品价格。在每一期期初,企业需要在满足服务水平约束的条件下同时决定订货量和产品价格。本文首先构建了动态定价和订购联合决策的随机动态规划模型,并证明了最优解的存在性。进一步,通过对最优解的结构进行刻画,将原问题的求解转化为若干子问题的求解,降低了问题求解的难度。通过对最优解的分析发现,当期初库存增大时,产品最优价格降低。通过分析目标服务水平对利润的影响,证明了服务水平与利润之间存在权衡,实现高的服务水平需要承受利润损失。数值模拟表明,相对于传统的静态定价策略,采用动态定价策略可以降低追求服务水平所带来的利润损失,验证了动态定价策略的有效性。  相似文献   

2.
李豪  彭庆  谭美容 《运筹与管理》2018,27(4):118-125
研究航空公司在需求学习下的动态定价策略。通过假设乘客到达率不确定以及具有策略等待行为,运用贝叶斯理论和博弈论对航空公司需求学习下的多周期动态定价问题进行建模,探讨了机票最优定价策略的充分条件,并通过分析航空公司收益函数的性质,得到了最优定价随时间和已出售机票数量的变化趋势。最后应用算例分析了需求学习的效果,得出:需求学习能够缓解需求不确定带来的损失,但不能完全消除;乘客策略程度越大,需求学习效果越明显。  相似文献   

3.
产品的双渠道销售不仅给企业带来更多的利润收益,同时给企业在应对市场复杂需求方面带来冲突和挑战.以拥有双渠道销售的制造商为研究对象,基于消费者对制造商线下渠道和线上渠道存在的策略型行为,研究了渠道之间考虑存在消费者转移的双渠道产品定价及协调策略.首先,构建了"线下主导"和"线上主导"的Stackelberg分散决策博弈模型,得到分散决策模式下的双渠道最优定价均衡解,并分析了策略型消费者所占比例、线上消费者购买到产品概率、消费者转移概率对最优定价和总利润的影响.然后,构建了双渠道集中决策定价模式,通过分析得出存在唯一的双渠道最优定价策略,并给出其解析解表达式.最后,通过数值算例仿真分析进行验证.  相似文献   

4.
随着互联网等新兴技术的发展,消费者对产品的价格追踪以及学习更加便利,其购买决策也会受到其他参与者决策的影响.消费者根据产品的上市价格和清仓时的可获得性决策购买时间,这种自身策略等待及受外部他人社交影响的行为加剧了市场需求的不确定性.承诺定价与差价补偿定价策略能有效地缓解消费者的策略等待行为,但相对动态定价策略缺少灵活性与便利性.因此文章研究零售商在动态定价、承诺定价、差价补偿定价策略中的选择问题.运用消费者偏好理论、博弈论和最优化理论求解各种模型的最优解及存在条件,进一步探讨消费者学习能力和社交影响对最优解的影响.结论表明,当消费者学习能力大于一定水平时,零售商应选择差价补偿定价,否则承诺定价为最优选择;消费者的学习能力增加了实体渠道的最优零售价和零售商整体利润,但降低了线上渠道的最优价格:社交影响有利于双渠道最优价格和零售商最优利润的增加.最后通过数值分析验证了上述模型的有效性和可靠性.  相似文献   

5.
研究了基于乘客分类的航空客运库存控制与动态定价策略.模型中,航空公司以提供折扣票的方式将乘客分为两类,并针对购买折扣票的乘客存在升级购买行为,通过动态的控制折扣票的销售和对机票实施动态定价来最大化自身的期望收益.应用动态规划建立了相应的收益管理模型,讨论了最优定价应满足的关系式,并得到了接受或拒绝乘客购买折扣票的阈值.最后,通过算例分析了升级购买概率对阈值、机票的价格及期望收益的影响.  相似文献   

6.
本文提出一种新的稳健资产负债模型最优化模型.该模型考虑了利率的不确定性对未来现金流、资金成本和资产收益率的影响.我们通过构建情景树反映未来的利率变化的情景结构.由于最优决策对利率的预测十分敏感,我们提出系数预测值可在一定误差范围内的稳健资产负债最优化模型.实证分析结果表明,从收益与风险均衡的角度看,稳健优化模型产生的保守解优于系数确定的优化模型产生的最优解.  相似文献   

7.
考虑在一个由双边平台、制造商和零售商组成的共享供应链中,研究双边平台匹配努力下的共享供应链动态定价问题。其中制造商通过平台共享其剩余产能,平台为动态地匹配制造商和零售商的供需资源而付出匹配努力,以此改变其服务水平,进而影响共享平台的交易费用、制造商的批发价格和零售商的零售价格。利用HJB方程构建微分博弈模型,分别探讨集中和分散式共享供应链中最优平台匹配努力和各成员的动态定价策略,得到不同情形下的动态定价轨迹,并分析了关键参数对定价策略的影响。结果表明,平台匹配努力通过影响其服务水平对最优/均衡解有正向影响,供应链各成员的定价策略取决于平台初始服务水平和稳态服务水平之间的关系。  相似文献   

8.
赵玲  刘志学 《运筹与管理》2022,31(6):105-110
为了吸引更多顾客,许多电子商务零售商允许顾客在一定时间内退货,导致其利润明显减少。同时,在补货时不仅产生依赖补货量的变动成本,而且会产生与补货量无关的固定成本。基于此,以最大化电子商务零售商的利润为目标,建立考虑顾客退货和固定成本的联合补货与定价模型,其中顾客的退货量与满足的需求呈正比。在一般需求情形下,部分刻画多期问题的最优策略;在特殊需求情形下,证明(s,S,p)策略对单期问题最优,并对多期问题的最优策略进行严格刻画。根据已有刻画为多期问题构造启发式策略。数值结果表明启发式策略近似最优;当初始库存水平足够高/低时,最优补货水平和定价随退货率与固定成本单调变化。关键词:联合补货与定价模型;顾客退货;固定成本;随机动态规划;最优策略  相似文献   

9.
为探寻存在搜寻成本情况下消费者购买可替代产品时的定价与库存问题,从消费者效用出发,对厂商收益构建了基于马尔可夫决策过程的优化模型。在消费者方面,分析了其购买与继续搜寻的条件,并分别在搜寻成本不变和搜寻成本边际递减的情况下研究了消费者保留效用的变化情况以及购买相应产品的概率。此外,与很多相关文献不同的是,由于搜寻成本的存在,该情形下的消费者并不一定会在完成购买之前搜寻完所有的产品。在厂商方面,根据实际情况构建不同搜寻顺序下的收益模型并求解出最优定价策略与库存策略,并将定价模型与库存策略扩展到了动态的环境,为厂商制定价格及库存方案提供相应的决策支持。  相似文献   

10.
考虑价格对需求量的扰动并利用贝叶斯公式对需求分布函数中的未知参数进行不断学习更新,研究缺货部分比例延迟交货情形下的动态库存与动态定价问题,刻画了最优利润函数的性质并证明了"基准库存列表价格"是最优的库存价格水平,并由此得到了最优的补货策略和定价策略。  相似文献   

11.
In this paper we consider a dynamic pricing model for a firm knowing that a competitor adopts a static pricing strategy. We establish a continuous time model to analyze the effect of dynamic pricing on the improvement in expected revenue in the duopoly. We assume that customers arrive to purchase tickets in accordance with a geometric Brownian motion. We derive an explicit closed-form expression for an optimal pricing policy to maximize the expected revenue. It is shown that when the competitor adopts a static pricing policy, dynamic pricing is not always effective in terms of maximizing expected revenue compared to a fixed pricing strategy. Moreover, we show that the size of the reduction in the expected revenue depends on the competitor’s pricing strategy. Numerical results are presented to illustrate the dynamic pricing policy.  相似文献   

12.
基于互联网的众包物流服务平台共享社会闲置人力资源,为电子商务O2O提供最后一公里配送服务。通过配送服务的动态定价来调控众包物流的社会配送供应能力,成为优化众包物流平台运营的重要手段。在众包物流平台激烈的竞争环境下,考虑到众包物流社会化配送供应能力的不确定性,采用动态优化理论,建立平台价格竞争下众包物流社会配送服务最优定价模型。运用汉密尔顿函数求解社会配送服务最优价格,研究众包物流社会配送服务供应能力随着价格变化的规律,进一步,分析众包物流平台竞争对最优价格变化规律的影响。数值仿真结果表明,众包物流社会配送服务价格增长率随着平台竞争的加剧而增加,可以有效调控众包物流服务的供应与需求平衡,优化众包物流平台的期望收益。  相似文献   

13.
While page views are often sold instantly through real-time auctions when users visit websites, they can also be sold in advance via guaranteed contracts. In this paper, we present a dynamic programming model to study how an online publisher should optimally allocate and price page views between guaranteed and spot markets. The problem is challenging because the allocation and pricing of guaranteed contracts affect how advertisers split their purchases between the two markets, and the terminal value of the model is endogenously determined by the updated dual force of supply and demand in auctions. We take the advertisers’ purchasing behaviour into consideration, i.e., risk aversion and stochastic demand arrivals, and present a scalable and efficient algorithm for the optimal solution. The model is also empirically validated with a commercial dataset. The experimental results show that selling page views via both channels can increase the publisher’s expected total revenue, and the optimal pricing and allocation strategies are robust to different market and advertiser types.  相似文献   

14.
Competition has a huge influence on customer buying behaviour and will impact on the optimal price that companies should charge for goods or services. To date, many dynamic pricing models have not modelled competition explicitly. In this paper, we introduce pricing strategies that maximize revenue when selling an inventory of identical items by a fixed time and where there is a competing seller. The model used incorporates a probabilistic formulation of customer demand, which is influenced by the prices offered by the company and the competitor, and the time remaining until the end of the selling period. Calculus of variations is used to solve the problem and simple conditions are given that ensure the uniqueness of a solution. Illustrative examples are included. A practical implementation that uses dynamic updating is proposed and tested using simulated data, showing the effectiveness of the method.  相似文献   

15.
In this paper, we present a comparative study on the total revenue generated with pre-emptive and non pre-emptive priority scheduler for a fairly generic problem of pricing the server’s surplus capacity in a single server Markovian queue. The specific problem is to optimally price the server’s surplus capacity by introducing a new class of customers (secondary class) without affecting the pre-specified service level of its current customers (primary class) when pre-emption is allowed. Pre-emptive scheduling is used in various applications. First, a finite step algorithm is proposed to obtain global optimal operating and pricing parameters for this problem. These optimal operating and pricing parameters constitute a unique Nash equilibrium in a certain two player non cooperative game. We then describe the range of service level where pre-emptive scheduling gives feasible solution and generates some revenue while non pre-emptive scheduling has infeasible solution. Further, some complementary conditions are identified to compare revenue analytically for certain range of service level where strict priority to secondary class is optimal. Our computational examples show that the complementary conditions adjust in such a way that pre-emptive scheduling always generates more revenue. Theoretical analysis is found to be intractable for the range of service level when pure dynamic policy is optimal. Hence, extensive numerical examples are presented to describe different instances. It is noted in numerical examples that pre-emptive scheduling generates at least as much revenue as non pre-emptive scheduling. A certain range of service level is identified where improvement in revenue is quite significant.  相似文献   

16.
We consider a continuous time dynamic pricing problem for selling a given number of items over a finite or infinite time horizon. The demand is price sensitive and follows a non-homogeneous Poisson process. We formulate this problem as to maximize the expected discounted revenue and obtain the structural properties of the optimal revenue function and optimal price policy by the Hamilton-Jacobi-Bellman (HJB) equation. Moreover, we study the impact of the discount rate on the optimal revenue function and the optimal price. Further, we extend the problem to the case with discounting and time-varying demand, the infinite time horizon problem. Numerical examples are used to illustrate our analytical results.  相似文献   

17.
Low-cost providers have emerged as important players in many service industries, the most predominant being low-cost, or the so-called discount airlines. This paper presents models and results leading toward understanding the revenue management outlook for a discount pricing firm. A framework and model is formulated specifically for the airline industry, but is generalizable to low-cost providers in similar revenue management settings. We formulate an optimal pricing control model for a firm that must underprice to capture a segment of exogenous demand. Two specific model formulations are considered: a continuous deterministic version, and a discrete stochastic version. Structural results are derived for the deterministic case, providing insight into the general form of optimal underpricing policies. The stochastic results support the structural insight from the deterministic solution, and illuminate the effect of randomness on the underpricing policies.  相似文献   

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