A dynamic two-segment partial backorder control of (r,Q) inventory system

Inventory management involves determination of shortage policy. It specifies the conditions for losing or backordering a demand. Alternative policies include pure backorder, pure lost sales, and partial backorder (using a single backorder control limit). When the backorder-cost is time dependent it makes sense to modify the backorder-limit over time. Thus, a new form of partial backorder policy (PB2) with two-segment backorder control limits is introduced. The traditional policies mentioned above, are special cases of PB2. Hence, we provide a unified framework for studying different policies that deal with shortage. The PB2 problem is formulated and solved as a discrete time, stochastic constrained control problem. Its performance is numerically compared with the simpler alternative policies. In some cases its cost savings, versus the best of PB and PL, exceeds 15%, and 7% versus a single backorder limit policy. The economical advantage is significant over a wide range of the problem parameters.Scope and purposeThis paper develops an expanded framework for modeling shortages in inventory management. It recognizes that optimal backordering strategy may change over time during an “out-of-stock” period. The paper is motivated by experience in the chemical industry in which, the cost of backordering is highly time related. Inventory managers, in this industry, consider to lose sales initially (once they run out of stock) and begin to backorder demand later as they approach the replenishment time. A two-segment partial backorder (r,Q) model is introduced and solved. Pure backorder (PB), pure lost sales (PL), and partial backorder (using a single backorder limit), are all special cases of the proposed model. The problem is formulated and solved as a discrete time, stochastic constrained control problem. Its performance is numerically compared with the simpler alternative policies. In some cases its cost savings, versus the best of PB and PL, exceeds 15%, and 7% versus a single backorder limit policy. The economical advantage is significant over a wide range of the problem parameters. The partial backorder policy we propose is not only different from those in the literature, but it provides new control flexibility.     

基于遗传算法的随机性（Q，r）库存系统仿真优化

（Q，r）模型是库存管理中的重要控制模型。对于随机性（Q，r）库存系统，难以用解析方法求解最优的库存控制策略。运用仿真优化技术，基于离散事件系统仿真原理，建立了随机性（Q，r）库存系统的仿真模型，设计了一种改进的遗传算法并应用它优化库存系统的库存控制策略。采用面向对象方法实现了仿真模型和改进的遗传算法。仿真实例表明所提出的仿真优化技术是可行且有效的。     

模糊随机决策环境下的核电站不常用条件(Q,r)库存模型

针对固定提前期内的需求为三角模糊变量,且用户总需求为梯形模糊随机变量的情形下,构建了不常用备件连续盘点模式下的（Q,r）模型,并推导出模糊成本最小化函数,进而利用基于模糊数期望值理论的去模糊化方法,求出最优订货点及订货量．最后,通过一个实例验证了模型的科学性和实用性．     

A novel strategy of pareto-optimal solution searching in multi-objective particle swarm optimization (MOPSO)

In multi-objective particle swarm optimization (MOPSO) algorithms, finding the global optimal particle (gBest) for each particle of the swarm from a set of non-dominated solutions is very difficult yet an important problem for attaining convergence and diversity of solutions. First, a new Pareto-optimal solution searching algorithm for finding the gBest in MOPSO is introduced in this paper, which can compromise global and local searching based on the process of evolution. The algorithm is implemented and is compared with another algorithm which uses the Sigma method for finding gBest on a set of well-designed test functions. Finally, the multi-objective optimal regulation of cascade reservoirs is successfully solved by the proposed algorithm.     

(Q,r,L) Inventory model with defective items

This paper assumes that an arrival order lot may contain some defective items, and the number of defective items is a random variable. We derive a modified mixture inventory model with backorders and lost sales, in which the order quantity, the reorder point and the lead time are decision variables. In our studies, we first assume that the lead time demand follows a normal distribution, and then relax the assumption about the form of the distribution function of the lead time demand and apply the minimax distribution-free procedure to solve the problem. We develop an algorithm procedure to obtain the optimal ordering strategy. Furthermore, the effects of parameters are also included.     

Ergodic distribution for a fuzzy inventory model of type (s, S) with gamma distributed demands

In this study, a stochastic process (X(t)), which describes a fuzzy inventory model of type (s, S) is considered. Under some weak assumptions, the ergodic distribution of the process X(t) is expressed by a fuzzy renewal function U(x). Then, membership function of the fuzzy renewal function U(x) is obtained when the amount of demand has a Gamma distribution with fuzzy parameters. Finally, membership function and alpha cuts of fuzzy ergodic distribution of this process is derived by using extension principle of L. Zadeh.     

Research of new strategies for improving CBR system

Case based reasoning (CBR), as an important AI technology, has gained popularity for its unique means of problem solving, which solves a new problem by remembering previous similar situations and reusing knowledge from the solutions to these situations. To construct a CBR system, two key issues have to be considered: one is feature selection, through which important features are extracted from the whole experience case and make up a case; the other is case retrieval, through which most appropriate case is retrieved for reuse. In order to further improve the accuracy of CBR system, this paper proposes a new feature selection method called Calculating Differences based on Growing Hierarchical Self Organizing Map clustering (CD-GHSOM) and a new case retrieval method called Growing Hierarchical Self Organizing Map based Case Retrieval (GHSOM-CR). Lots of experiments are implemented to validate the effectiveness of the proposed methods by comparing them with other recent researches.     

基于混合差分进化算法和熵权TOPSIS的多目标(Q, r)库存模型

讨论随机需求环境下的多目标库存控制问题,构建以成本、缺货率和缺货量3个指标最小化为准则的多目标（Q,r）库存模型．为了求出决策者需要的Pareto前沿,设计了基于遗传和差分进化算法的混合智能算法来产生非支配解,进而利用基于熵权的TOPSIS方法对最优解进行排序,此结果可为管理者提供有益的决策参考．     

Solutions to the functional equation I(x, y) = I(x, I(x, y)) for three types of fuzzy implications derived from uninorms

This paper investigates an iterative Boolean-like law with fuzzy implications derived from uninorms. More precisely, we characterize the solutions to the functional equation I(x, y) = I(x, I(x, y)) that involve RU-, (U, N)- and QLU-implications generated by the most usual classes of uninorms.     

Optimal strategies for an inventory system with cost functions of general form

For an inventory system with a continuous compact phase state and control set, the existence of the optimal (S, s)-policy is proved and an algorithm for determination of this policy based on stochastic approximation is presented. The cost functions are monotone, continuous, and of a rather general form. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 106–123, July–August, 1999.     

Growth and electrical properties of highly (0 0 1)-oriented Pb(Zr0.52Ti0.48)O3 thin films on amorphous TiN buffered Si(1 0 0)

Pb(Zr_0.52Ti_0.48)O₃ (PZT) ferroelectric thin films with LaNiO₃ (LNO) as bottom electrodes have been grown on amorphous TiN buffered Si(1 0 0) substrates by pulsed laser deposition. It was found that highly (0 0 1)-oriented LNO films could be obtained even if TiN underlayers were amorphous. XRD analyses showed that the subsequently deposited PZT films were also preferentially (0 0 1)-oriented due to the template effect of the perovskite structured LNO films. Dielectric constant of the PZT thin films remained almost constant with frequency in the range from 10³ to 10⁶ Hz, and tangent loss was as small as 0.02 at high frequencies. The remnant polarization and coercive field of an Au/PZT/LNO capacitor were typically 20 μC/cm² and 30 kV/cm, respectively. C–V and I–V characteristics revealed the capacitance and leakage current variations with applied voltage were asymmetric when the bottom electrode was negatively as well as positively biased, indicating that ferroelectric/electrode interfaces and space charges play an important role in the electrical properties of ferroelectric capacitors.     

Design,fabrication, and testing of a 3-DOF HARM micromanipulator on (1 1 1) silicon substrate

In this study, a novel HARM (high aspect ratio micromachining) micromanipulator fabricated on (1 1 1) silicon wafer is reported. The micromanipulator consists of a positioning stage, a robot arm, supporting platforms, conducting wires, and bonding pads. These components are monolithically integrated on a chip through the presented processes. The three-degrees-of-freedom (3-DOF) positioning of the micromanipulator is realized by using the integration of two linear comb actuators and a vertical comb actuator. The robot arm is used to manipulate samples with dimension in the order of several microns to several hundred microns, for instance, optical fibers and biological samples. The robot arm could be a gripper, a needle, a probe, or even a pipette. Since the micromanipulator is made of single crystal silicon, it has superior mechanical properties. A micro gripper has also been successfully designed and fabricated.     

等价树的双环网络G(N;r,s)的研究

基于前人提出的双环网络G(N;r,s)的分步直径求解法,提出了一个等价树直径求解方法,得到一个新的研究双环网络的拓扑结构-等价树;研究了双环网络等价树的性质并给出了等价树的构造算法;给出了双环网络直径d(N;r,s)的显示公式;利用C#编程语言对等价生成树的结构模型进行了仿真实现;对任意给定的N,1≤r≠s相似文献   

An artificial neural network (p, d, q) model for timeseries forecasting

Artificial neural networks (ANNs) are flexible computing frameworks and universal approximators that can be applied to a wide range of time series forecasting problems with a high degree of accuracy. However, despite all advantages cited for artificial neural networks, their performance for some real time series is not satisfactory. Improving forecasting especially time series forecasting accuracy is an important yet often difficult task facing forecasters. Both theoretical and empirical findings have indicated that integration of different models can be an effective way of improving upon their predictive performance, especially when the models in the ensemble are quite different. In this paper, a novel hybrid model of artificial neural networks is proposed using auto-regressive integrated moving average (ARIMA) models in order to yield a more accurate forecasting model than artificial neural networks. The empirical results with three well-known real data sets indicate that the proposed model can be an effective way to improve forecasting accuracy achieved by artificial neural networks. Therefore, it can be used as an appropriate alternative model for forecasting task, especially when higher forecasting accuracy is needed.     

Computing (r, Q) policy for an inventory system with limited sharable resource

This paper deals with inventory systems with limited resource for a single item or multiple items under continuous review (r, Q) policies. For the single-item system with a stochastic demand and limited resource, it is shown that an existing algorithm can be applied to find an optimal (r, Q) policy that minimizes the expected system costs. For the multi-item system with stochastic demands and limited resource commonly shared among all items, an optimization problem is formulated for finding optimal (r, Q) policies for all items, which minimize the expected system costs. Bounds on the parameters (i.e., r and Q) of the optimal policies and bounds on the minimum expected system costs are obtained. Based on the bounds, an algorithm is developed for finding an optimal or near-optimal solution. A method is proposed for evaluating the quality of the solution. It is shown that the algorithm proposed in this paper finds a solution that is (i) optimal/near-optimal and/or (ii) significantly better than the optimal solution with unlimited resource.     

A method for exact reliability of consecutive2-out-of-(r, r)-from-(n, n):F systems

A new reliability model, consecutive 2‐out‐of‐(r, r)‐from‐(n, n):F model, is proposed. The consecutive 2‐out‐of‐(r, r)‐from‐(n, n):F system consists of a square grid of side n (containing n² components) such that the system fails if and only if there is at least one square of side r which includes among them at least two failed components. For i.i.d. case an algorithm is given for computing the reliability of the system. The reliability function can be expressed by the number of 0–1 matrices having no two or more 0s at any square of side r.     

A recursive algorithm for the reliability of a circular connected-(r,s)-out-of-(m,n):F lattice system

A circular connected-(r, s)-out-of-(m, n):F lattice system consists of m×n components arranged in a cylindrical grid. Each of m circles has n components, and this system fails if and only if there exists a grid of size r ×s which all components are failed. A circular connected-(r, s)-out-of-(m, n):F lattice system might be used in reliability models for ‘Feelers for measuring temperature on reaction chamber’ and ‘TFT Liquid Crystal Display system with 360° wide area’.In this study, we proposed a new recursive algorithm for obtaining the reliability of a circular connected-(r, s)-out-of-(m, n):F lattice system. We evaluated our proposed algorithms in terms of computing time and memory capacity. Furthermore, a numerical experiment comparing our proposed algorithm with Yamamoto and Miyakawa's algorithm [Yamamoto, H., & Miyakawa, M. (1996). Reliability of circular connected-(r, s)-out-of-(m, n):F lattice system. Journal of the Operations Research Society of Japan, 39(3), 389–406] showed that our proposed algorithm is more effective for systems with a large n.     

Developing economic order quantity model for non-instantaneous deteriorating items in vendor-managed inventory (VMI) system

This paper develops an economic order quantity model for non-instantaneous deteriorating items with and without shortages to investigate the performance of the vendor-managed inventory (VMI) system. This model is developed for a two-level supply chain consisting of a single supplier and single retailer with a single non-instantaneous deteriorating item. A numerical example and sensitivity analysis are provided to illustrate how increasing or reducing the related parameters change the optimal values of the decision variables of the two proposed models. The results show that VMI works better and charges lower cost in all conditions.     

Comparisons of motion‐blur assessment strategies for newly emergent LCD and backlight driving technologies

Abstract— Compared to the conventional cathode‐ray‐tube TV, the conventional liquid‐crystal TV has the shortcoming of motion blur. Motion blur can be characterized by the motion‐picture response‐time metric (MPRT). The MPRT of a display can be measured directly using a commercial MPRT instrument, but it is expensive in comparison with a photodiode that is used in temporal‐response (temporal luminance transition) measurements. An alternative approach is to determine the motion blur indirectly via the temporal point‐spread function (PSF), which does not need an accurate tracking mechanism as required for the direct “spatial” measurement techniques. In this paper, the measured motion blur is compared by using both the spatial‐tracking‐camera approach and the temporal‐response approach at various backlight flashing widths. In comparison to other motion‐blur studies, this work has two unique advantages: (1) both spatial and temporal information was measured simultaneously and (2) several temporal apertures of the display were used to represent different temporal PSFs. This study shows that the temporal method is an attractive alternative for the MPRT instrument to characterize the LCD's temporal performance.     

On the performance of (1, λ)-evolution strategies for theridge function class

This paper presents the N-dependent analysis of the (1, λ)-evolution strategy (ES) with isotropic mutations for the ridge functions including the special cases of sharp and parabolic ridges. The new approach presented allows for the prediction of the dynamics in ridge direction as well as in radial direction. The central quantities are the corresponding progress rates which are determined in terms of analytical expressions. Its predictive quality is evaluated by ES simulations and the steady-state behavior is discussed in detail