随机需求下的供应链库存控制策略研究

考虑了由多个供应商、一个配送中心组成的二级供应链系统在市场需求为随机情况下的多品种库存问题。通过确定各变量之间的关系,以配送中心损失期望值最小为目标函数,建立了一个混合整数非线性规划模型;利用求解多元函数条件极值的办法来求解该问题模型;最后给出了一个算例进一步诠释了该解法,从而丰富了在面对市场为随即需求下的多品种库存控制策略的研究工作。     

Robust supply chain design under uncertain demand in agile manufacturing

This paper considers a supply chain design problem for a new market opportunity with uncertain demand in an agile manufacturing setting. We consider the integrated optimization of logistics and production costs associated with the supply chain members. These problems routinely occur in a wide variety of industries including semiconductor manufacturing, multi-tier automotive supply chains, and consumer appliances to name a few. There are two types of decision variables: binary variables for selection of companies to form the supply chain and continuous variables associated with production planning. A scenario approach is used to handle the uncertainty of demand. The formulation is a robust optimization model with three components in the objective function: expected total costs, cost variability due to demand uncertainty, and expected penalty for demand unmet at the end of the planning horizon. The increase of computational time with the numbers of echelons and members per echelon necessitates a heuristic. A heuristic based on a k-shortest path algorithm is developed by using a surrogate distance to denote the effectiveness of each member in the supply chain. The heuristic can find an optimal solution very quickly in some small- and medium-size cases. For large problems, a “good” solution with a small gap relative to our lower bound is obtained in a short computational time.     

过度自信和需求不确定性对库存系统的影响

研究过度自信和需求不确定性对库存系统的影响。通过引入一个均值增加、方差缩小的变换来定量刻画决策者的过度自信水平,得到系统最优订货量和最优利润关于过度自信水平和单位缺货惩罚的单调性。证明随机大的需求会导致较高的最优订货批量,系统最优订货量在割准则序意义下具有随机单调性,并给出了比较系统最优订货量的充分或充分必要条件。进一步,运用标准化随机变量的变换证明了在高利润环境下系统利润将随着需求可变性的增加而减少。     

随机需求下双渠道供应链库存动态交互优化

针对双渠道供应链库存系统导致的缺货与库存积压等问题，在线上线下均为随机需求的条件下，考虑生产延迟和物流延迟，建立了双渠道库存的单独控制、集中控制和交叉补货控制这三种模式的动态优化模型。首先，以库存动态微分方程为基础，创新性地以控制理论为指导思想，以泰勒展开和拉普拉斯变换为手段，得到双渠道库存系统的反馈传递函数；其次，考虑了交叉补货的进销存过程中的周期间交互、上下游间交互以及渠道间交互，利用延迟控制、反馈控制和比例-积分-微分（PID）控制构造了双输入、双输出的复杂交互系统，以此寻求双渠道库存系统自身以及渠道间的动态供需双平衡，优化双渠道库存持有量，降低缺货次数和缺货量并使其保持动态稳定状态；最后，通过数值仿真实验，对比三种双渠道库存控制策略。仿真结果表明，在线上线下渠道为不同分布的随机需求时，交叉补货控制的剩余库存比独立库存控制降低了4.9%，交叉补货控制的缺货率与独立控制和集中控制相比分别下降了66.7%和60%。实验结果表明，在线上线下渠道为不同分布的随机需求的情况下使用双渠道交叉补货策略能很好地降低库存持有量，减少缺货次数和缺货量，从而节约库存成本。     

随机需求下双渠道供应链库存动态交互优化

针对双渠道供应链库存系统导致的缺货与库存积压等问题,在线上线下均为随机需求的条件下,考虑生产延迟和物流延迟,建立了双渠道库存的单独控制、集中控制和交叉补货控制这三种模式的动态优化模型。首先,以库存动态微分方程为基础,创新性地以控制理论为指导思想,以泰勒展开和拉普拉斯变换为手段,得到双渠道库存系统的反馈传递函数;其次,考虑了交叉补货的进销存过程中的周期间交互、上下游间交互以及渠道间交互,利用延迟控制、反馈控制和比例-积分-微分（PID）控制构造了双输入、双输出的复杂交互系统,以此寻求双渠道库存系统自身以及渠道间的动态供需双平衡,优化双渠道库存持有量,降低缺货次数和缺货量并使其保持动态稳定状态;最后,通过数值仿真实验,对比三种双渠道库存控制策略。仿真结果表明,在线上线下渠道为不同分布的随机需求时,交叉补货控制的剩余库存比独立库存控制降低了4.9%,交叉补货控制的缺货率与独立控制和集中控制相比分别下降了66.7%和60%。实验结果表明,在线上线下渠道为不同分布的随机需求的情况下使用双渠道交叉补货策略能很好地降低库存持有量,减少缺货次数和缺货量,从而节约库存成本。     

Infinite-horizon models for inventory control under yield uncertainty and disruptions

We consider a firm facing supply chain risk in two forms: disruptions and yield uncertainty. We demonstrate the importance of analyzing a sufficiently long time horizon when modeling inventory systems subject to supply disruptions. Several previous papers have used single-period newsboy-style models to study supply disruptions, and we show that such models underestimate the risk of supply disruptions and generate sub-optimal solutions. We consider one case where a firm's only sourcing option is an unreliable supplier subject to disruptions and yield uncertainty, and a second case where a second, reliable (but more expensive) supplier is available. We develop models for both cases to determine the optimal order and reserve quantities. We then compare these results to those found when a single-period approximation is used. We demonstrate that a single-period approximation causes increases in cost, under-utilizes the unreliable supplier, and distorts the order quantities that should be placed with the reliable supplier in the two-supplier case. Moreover, using a single-period model can lead to selecting the wrong strategy for mitigating supply risk.     

A belief-rule-based inventory control method under nonstationary and uncertain demand

This paper is devoted to investigating inventory control problems under nonstationary and uncertain demand. A belief-rule-based inventory control (BRB-IC) method is developed, which can be applied in situations where demand and demand-forecast-error (DFE) do not follow certain stochastic distribution and forecasting demand is given in single-point or interval styles. The method can assist decision-making through a belief-rule structure that can be constructed, initialized and adjusted using both manager’s knowledge and operational data. An extended optimal base stock (EOBS) policy is proved for initializing the belief-rule-base (BRB), and a BRB-IC inference approach with interval inputs is proposed. A numerical example and a case study are examined to demonstrate potential applications of the BRB-IC method. These studies show that the belief-rule-based expert system is flexible and valid for inventory control. The case study also shows that the BRB-IC method can compensate DFE by training BRB using historical demand data for generating reliable ordering policy.     

Robust control under parametric uncertainty via primal-dual convexanalysis

A numerical method is proposed for optimal robust control synthesis. The method applies to the case when the coefficients of the characteristic polynomial depend linearly on the uncertain parameters. A primal/dual pair of infinite-dimensional convex problems is solved by successive finite-dimensional approximations. The primal/dual pair has no duality gap, and both upper and lower bounds produced by the approximations converge monotonically to the optimal value     

需求不确定条件下柔性供应链生产决策模型及优化

研究需求不确定条件下柔性供应链生产决策优化问题，以供应链期望总成本最小化为目标函数，考虑生产柔性为约束条件，建立了柔性供应链生产决策模型；通过优化分析，给出了供应链生产柔性有效边界的定义和经济意义，在此基础上引入成本柔性系数最小化的判断标准，从而得到最优方案的确定方法，最后通过算例对模型进行了验证。     

需求不确定下考虑网络营销的供应链决策模型

利用报童理论和退货政策模型,研究了传统市场与电子商务市场的内在关系,建立了供应商参与两种市场联合营销情况下的供应链管理模型.重点分析了供应商如何在电子商务环境下组织生产,如何通过实施协作提高供应链总利润,如何评估两种市场上的销售策略.最后采用算例分析的方法,证明了模型和算法的有效性和可行性.     

Stationary inventory control policies in supply systems under inflation conditions

This paper considers the feasibility of using the optimal parameters of stationary inventory control policies to design inventory control rules in supply systems operating on a real market. The efficiency of the long-sighted and myopic inventory control policies is compared. Different approaches to design the optimal stationary policies are investigated. A comparative evaluation of these approaches is given and the specifics of their application are discussed. The optimal parameters of the stationary inventory control policies as functions of the market state and, in particular, of the inflation rate are estimated via simulation experiments.     

Robust control of a linear object under parametric uncertainty

A robust control problem for a linear nonstationary system under condition of incomplete information about its parameters is considered. Problems of robust and d-robust stabilization are formulated, and conditions of existence of their solutions are found. To construct robust control, minimax technique is used. Conditions of equivalence of solutions to the classical control problem and to that in the minimax formulation are determined.     

时滞不确定采样控制系统的鲁棒稳定性

本文给出了一种可定量分析采样控制系统的时滞鲁棒稳定性的方法.因为采样系统的对象是连续时间的,所以对象中的时滞也应该是按连续时间来处理.文中指出,一个整数倍时滞是稳定的采样系统,可能会因为有并不很大的连续时间时滞而失稳.定义了一个新的变量w(t),用来描述这个不确定连续时间时滞带来的动特性.将w(t)的反馈回路分成与时滞无关和有关的两个部分,并提出了一种用频率响应来确定是否存在由不确定时滞引起的周期解的方法.用修正z-变换法和仿真验证了这个由图解解析所求得的解.本方法既可用于采样系统,也可用于一般的连续时间系统.     

Robust control under parametric uncertainty: An overview and recent results

Modern Robust Control has had two distinct lines of development: (a) Robustness through quadratic optimization and (b) Robustness under parametric uncertainty. The first approach consists of Kalman’s Linear Quadratic Regulator and H_∞ optimal control. The second approach is the focus of this overview paper. It provides an account of both analysis as well as synthesis based results. This line of results was sparked by the appearance of Kharitonov’s Theorem in the early1980s. This result was rapidly followed by further results on the stability of polytopes of polynomials such as the Edge Theorem and the Generalized Kharitonov Theorem, stability of systems under norm bounded perturbations and the computation of parametric stability margins. Many of these analysis results established extremal testing sets where stability or performance would breakdown. Starting in 1997, when it was established that high order controllers were fragile, attention turned to the synthesis and design of the parameters of low order controllers such as three term controllers and more particularly Proportional-Integral-Derivative (PID) controllers. An extensive theory of design of such systems has developed in the last twenty years. We provide a summary without proofs, of many of these results.     

Ordering,wholesale pricing and lead-time decisions in a three-stage supply chain under demand uncertainty

This paper develops a game theoretic model of a three-stage supply chain consisting of one retailer, one manufacturer and one subcontractor to study ordering, wholesale pricing and lead-time decisions, where the manufacturer produces a seasonal/perishable product. We explicitly model the effects of the lead-time and the length of selling season on both demand uncertainty and inventory-holding costs. We present the equilibrium outcome of the decentralized supply chain. When the lead-time increases, we find that the retailer increases the order quantity, the manufacturer offers a lower unit-wholesale price and the subcontractor decreases its unit-wholesale price if the manufacturer subcontracts part of the retailer’s order. In the endogenous lead-time setting, we illustrate the effects of some factors such as unit holding cost and capacity on the equilibrium outcome. We find that a higher unit holding cost implies a lower optimal lead-time and order quantity while higher unit-wholesale prices; the basic demand uncertainty increases the optimal lead-time and order quantity while decreases the unit-wholesale prices. The effects of distribution form on equilibrium outcome/profits are investigated by employing a numerical example. The profit loss of decentralization decreases (increases) with the basic demand uncertainty and manufacturer’s capacity (mean demand).     

基于增广泛函的混合时滞区间神经网络的鲁棒稳定性

本文针对一类带有混合时变时滞 (离散和分布时滞)的区间递归神经网络进行了全局鲁棒稳定性研究.与之前的处理方法不同,在本文中通过使用一种新型的增广Lyapunov-Krasovskii泛函,从而得到了一类新颖的关于区间递归神经网络的时滞依赖全局鲁棒稳定性判据.在新的增广泛函中,由于首次使用了带有激活函数的积分项,系统状态和激活函数之间的关系将被更好地表示出来.因此,本文提出的判据具有更小的保守性.同时,在本文提出的判据中,放松了时变时滞变化率必须小于1的限制.仿真结果进一步证明了本文结果的有效性.     

需求分布不确定条件下的多周期库存鲁棒优化模型

在离散需求情景概率不确定的条件下, 建立基于最大最小方法的多周期库存鲁棒优化模型. 考虑需求分布分别隶属于区间和椭球不确定集两种情形, 运用对偶理论将多周期库存鲁棒优化模型转化为易于求解的凸规划问题. 数值结果表明, 与已知需求分布下的系统最优绩效相比, 采用鲁棒订货策略虽然会导致部分绩效损失, 但损失值很小, 表明基于鲁棒优化的多周期库存订货策略具有良好的鲁棒性, 能够有效抑制需求分布不确定性对库存运作绩效的影响.

     

Multi-objective optimization for inventory control in two-level assembly systems under uncertainty of lead times

Supply planning for two-level assembly systems under lead time uncertainties is considered. It is supposed that the demand for the finished product and its due date are known. The assembly process at each level begins when all necessary components are in inventory. A holding cost at each level appears if some components needed to assemble the same semi-finished product arrive before beginning the assembly at this level. It is assumed also that the component lead time is a random discrete variable. The objective is to find the release dates for the components at level 2 in order to minimize the expected component holding costs and to maximize the customer service level for the finished product. For this new problem, we consider two multi-objective approaches, which are both based on genetic algorithms. They are evaluated with a variety of supply chain settings, and their respective performance is reported and commented. These two heuristics permitted to obtain interesting results within a reasonable computational time.     

Optimization of robust area traffic control with equilibrium flow under demand uncertainty

For area traffic control road network under realization of uncertain travel demand, a robust signal setting is investigated in this paper. Due to certain hierarchy in a decision-making order, a min–max bilevel program is proposed. A new solution method is presented to determine a Nash–Stackelberg solution where a proposed signal setting is found for area traffic control under demand uncertainty. In order to investigate the robustness of the proposed signal settings, numerical computations are performed for various initial data sets in a medium-sized example road network. Good computational results indicated that the proposed signal settings can successfully reduce a worst-case travel cost substantially while incurring a relatively slight loss of optimality with respect to the optimal deterministic solutions for nominal travel demands. Particularly, our computation results showed that the proposed signal settings become even attractive as demand growth increases under a worst-case realization taken by uncertain travel demands.