快速补货模式下的动态定价与库存联合策略

在供应有限的情况下,研究常规补货和快速补货下商品动态定价问题.首先,建立了动态规划模型,理论证明了最优库存策略是基于(s,S)策略下改进的基本库存策略.其次,提出了一种启发式策略求复杂系统的最优策略,启发式算法能够求出最优价格和最优库存水平.最后,数值算例研究表明,库存管理中采用快速补货提高了零售商的利润;初始库存水平越高零售商的利润越高.     

考虑预付定金和退货的SMPEs产品定价与优化策略

借鉴中小制造型企业(SMPEs)在线渠道预售模式,考虑市场中存在预付订金和不预付订金的顾客,并将其退货情况引入到生产商利润表达式中,构建确定性和随机性市场需求下的SMPEs产品销售利润最大化模型,推导生产商产品最优定价的解析解;对比两种销售模式的利润,得到了生产商选择不同销售策略的条件。进一步考虑预付定金的产品数量、预交定金比例、退货数量是关于价格折扣敏感的情况,采用拉格朗日乘子法对生产商产品定价及优化问题进行研究,分析求得生产商销售策略(产品定价和价格折扣)的近似最优解。最后,通过数值算例对研究结论进行了验证并给出经济学解释。     

考虑跨渠道退货的双渠道零售商定价与退货策略研究

本文以零售商线上线下销售和消费者退货并存的销售模式为背景,以零售商利润最大化为目标,构建线上线下统一定价和自主定价的双渠道和跨渠道退货两种不同的定价决策模型,分析了顾客渠道偏好和退货麻烦成本对零售商定价和退货策略选择与利润的影响。研究发现：给定退货麻烦成本,当顾客渠道偏好明显时,零售商应采取自主定价策略,否则应采取统一定价策略。顾客偏好线上渠道时,应该采取跨渠道退货政策;顾客偏好线下渠道时,应采取双渠道退货政策。零售商应根据顾客渠道偏好和退货麻烦成本选择合理的定价策略和退货策略,保证其利润最大化。本文研究对于采用线上线下渠道销售并允许退货的零售商设置最合理的退货方式和最优定价策略有一定的实际应用价值。     

考虑顾客策略行为和机器故障的加工排队系统最优定价

在加工系统中,顾客的决策行为不仅受价格影响,同时对交货时间敏感,而且不同的顾客对时间具有不同的敏感程度。本文采用排队理论,研究了垄断环境中策略顾客行为和机器故障干扰的加工系统最优定价问题,证明了最优定价的存在性,设计了最优定价的求解方法。通过数值算例,讨论了实际需求比例、最优定价和最大利润关于加工成本、单位时间维修成本、机器故障频率和平均维修时间的变化规律。数值结果说明机器故障修复时间增加比故障频率增加对企业利润造成影响更大。     

电子商务环境下定价与退货策略整合优化研究

在电子商务供应链环境下,顾客直接从电子市场采购商品,失去了现场检查商品性能与质量的机会,结果造成顾客对所购商品不满意甚至退货的可能性增加.一个清晰、优惠的退货条例会受到顾客的欢迎,增加市场需求,提升企业的竞争力,然而,对制造厂家来说既可能增加收入,也可能增加退货成本.本文以商品价格和退货退款为决策变量,建立企业利润最大化模型,以此为依据企业可获得最优的定价和退货退款比例,使得从事电子商务的经理们有了使企业获得最大利润的理论依据.最后,指出了未来可能的几个研究方向.     

VMCI下考虑顾客退货的供应链联合促销与协调

在允许顾客退货的环境下,以供应商管理寄售库存(VMCI)的供应链为对象,探讨了供应链的促销决策及协调问题。研究发现,集中情景下最优的寄售库存量与促销水平均高于分散情景下的对应值;根据在供应链运营过程中双方成员承担的不同风险设计的滞销补贴-双向促销成本分担契约可以实现供应链协调;期望退货费用不超过某一阈值时,全额退货策略优于不允许退货策略。此外,通过数值仿真揭示了顾客评估风险对利润及协调契约的影响。     

考虑服务和退货的双渠道供应链定价问题研究

在考虑零售服务和消费者退货情况下,运用两阶段优化方法分别探究了集中式和分散式两种双渠道供应链的最优定价策略。研究发现零售服务有助于提高零售商的渠道权力,并始终使制造商获益,但只有当服务水平小于某一临界值时,才使制造商和零售商同时得到帕累托改进。零售价格和直销价格与退货率正相关,而与服务水平的关系受渠道结构的影响。服务水平的提高加剧了供应链的“双重边际化”效应,制造商通过生产与消费者需求相匹配的产品来降低退货风险可以减弱这种效应,从而提高供应链效率。     

竞争环境下考虑顾客惰性行为的易逝品动态定价

消费者购买决策的行为倾向对企业的收益管理有着不可忽视的影响。本文在竞争企业动态定价问题中, 考虑了顾客惰性行为——即顾客购买决策的非理性拖延倾向——的影响。证明了库存充足情况下, 多企业多期博弈各销售期都存在唯一的纯策略纳什均衡。数值模拟表明, 顾客惰性对企业的最优价格和企业最大期望收益均造成负面影响, 且对销售低质量产品的企业的负面影响更大。此外, 顾客惰性宽度对各企业最优价格和最大期望收益的影响边际效应递增, 而顾客惰性深度产生的影响边际效应递减。     

两阶段下批发商对于策略型顾客的最优定价和库存管理

对于农产品或者易于腐坏的其加工品,长时间存放需要在冷库中储存保鲜,假设零售商分两个阶段出售此种单一商品,第一阶段取一定数量出售,剩下的商品储存起来至第二阶段出售.文章基于策略型顾客的行为,确定零售商在售卖季开始之前的最优订货量,在第一阶段出售商品的最优数量,第一阶段和第二阶段商品的最优定价.另外,给定零售商决策的情况下...     

考虑退货策略和贸易信贷的库存运营策略选择研究

在贸易信贷背景下,研究了退货策略对供应链和供应链中各成员库存运营策略选择的影响,把不提供退货策略作为基准,通过建立模型求解表明:无论是否提供退货策略,供应链和供应链中各成员都会选择零售商管理库存的库存运营策略,并且提供退货策略要始终优于不提供退货策略;贷款利率对零售价、订购量和供应链利润无影响,对批发价和供应商的利润有...     

Controlled jump processes

Finite and infinite planning horizon Markov decision problems are formulated for a class of jump processes with general state and action spaces and controls which are measurable functions on the time axis taking values in an appropriate metrizable vector space. For the finite horizon problem, the maximum expected reward is the unique solution, which exists, of a certain differential equation and is a strongly continuous function in the space of upper semi-continuous functions. A necessary and sufficient condition is provided for an admissible control to be optimal, and a sufficient condition is provided for the existence of a measurable optimal policy. For the infinite horizon problem, the maximum expected total reward is the fixed point of a certain operator on the space of upper semi-continuous functions. A stationary policy is optimal over all measurable policies in the transient and discounted cases as well as, with certain added conditions, in the positive and negative cases.     

Fixed-time schedules for the processing of jobs when service completions are not observable

We argue the importance of studying service systems in which the successful completion of job/customer service cannot be observed contemporaneously. Military and other applications are cited. The allocation of a large amount of processing to a job may make its (unobservable) successful completion more likely but will impose a burden on other jobs awaiting service. A fixed-time schedule specifies both the order in which jobs should be processed and how much processing each should receive. The goal is to find schedules which maximise the total expected reward earned from all jobs served. While this problem is intractable in general, a range of characterisations of optimal fixed-time schedules is achieved for given scenarios. The development of effective heuristics is also discussed.Received: November 2004 / Revised: January 2005In honour of the 60th birthday of Professor Ulrich Rieder     

Multiperiod Portfolio Optimization with Terminal Liability: Bounds for the Convex Case

This paper is concerned with an investor trading in multiple securities over many time periods in order to meet an outstanding liability at some future date. The investor is concerned with maximizing the expected profits from portfolio rebalancing under an initial wealth restriction to meet the future liabilities. We formulate the problem as a discrete-time stochastic optimization model and allow asset prices to have continuous probability distributions on compact domains. For the case of Markovian price uncertainty and convex terminal liability, we develop a simplicial approximation, under which bounds on the problem can be computed efficiently. Computations only require evaluating a dynamic programming recursion, which thus, allows its application to problems with a large number of trading periods. The bounds are tight in that they are exact in certain cases. Numerical results are given to demonstrate the computational efficiency of the procedure.     

Optimal Security Liquidation Algorithms

This paper develops trading strategies for liquidation of a financial security, which maximize the expected return. The problem is formulated as a stochastic programming problem that utilizes the scenario representation of possible returns. Two cases are considered, a case with no constraint on risk and a case when the risk of losses associated with trading strategy is constrained by Conditional Value-at-Risk (CVaR) measure. In the first case, two algorithms are proposed; one is based on linear programming techniques, and the other uses dynamic programming to solve the formulated stochastic program. The third proposed algorithm is obtained by adding the risk constraints to the linear program. The algorithms provide path-dependent strategies, i.e., the fraction of security sold depends upon price sample-path of the security up to the current moment. The performance of the considered approaches is tested using a set of historical sample-paths of prices.     

具有不同生产时区费用的单机可拒绝排序问题

考虑了单机环境下,机器具有不同的生产时区费用,并且工件的加工是可以拒绝的排序问题.需要选择要加工的工件集合,对每个加工的工件指派相应的生产区间并排序,并支付拒绝加工工件的拒绝费用.对于排序理论中主要的四个目标函数,研究了单位区间的生产费用随着时间的推迟是单调非增的情况,分析了问题的复杂性,对于这些问题给出了它们的最优算法.     

Optimal nonlinear feedback control of quasi-Hamiltonian systems

An innovative strategy for optimal nonlinear feedback control of linear or nonlinear stochastic dynamic systems is proposed based on the stochastic averaging method for quasi-Hamiltonian systems and stochastic dynamic programming principle. Feedback control forces of a system are divided into conservative parts and dissipative parts. The conservative parts are so selected that the energy distribution in the controlled system is as requested as possible. Then the response of the system with known conservative control forces is reduced to a controlled diffusion process by using the stochastic averaging method. The dissipative parts of control forces are obtained from solving the stochastic dynamic programming equation. Project supported by the National Natural Science Foundation of China (Grant No. 19672054) and Cao Guangbiao High Science and Technology Development Foundation of Zhejiang University.     

On the evaluation of fixed permutations as strategies in stochastic scheduling

A general model is proposed for the stochastic version of the single-machine allocation problem. Sufficient conditions are given to ensure that there is an optimal strategy given by a fixed permutation of the job set. Additional results are given for an important special case of the general model involving simple jobs. The paper concludes with material concerning the evaluation of fixed permutations as strategies under conditions more general than the sufficient conditions mentioned above.