异构总线网络的可分负载优化调度算法

研究了异构总线网络的负载优化调度问题,详细讨论了处理机选择、任务分配顺序和各处理机分配任务数量。结论表明：通过按照处理机速度递减的顺序配置处理机,并据此分配相应的任务,即可实现负载的优化调度。     

一种利用切比雪夫逼近求解库存最优控制的方法

针对供应链中库存随着需求的变化可能导致的积压和对生产(或采购)产生的不利影响,为更好地协调生产(或采购)并减少产品库存,研究了一类基于库存约束和动态时变需求下的多品种、多周期、多循环的生产与库存的最优控制模型.结合最优控制理论,给出一种采用切比雪夫多项式逼近和高斯-切比雪夫数值积分对库存最优控制问题进行数值求解的方法.实例分析表明该方法是可行的.     

The governing dynamics of supply chains: The impact of altruistic behaviour

This paper analyses an infinite horizon two-echelon supply chain inventory problem and shows that a sequence of the optimum ordering policies does not yield globally optimal solutions for the overall supply chain. First-order autoregressive demand pattern is assumed and each participant adopts the order-up-to (OUT) policy with a minimum mean square error forecasting scheme to generate replenishment orders. To control the dynamics of the supply chain, a proportional controller is incorporated into the OUT policy, which we call a generalised OUT policy. A two-echelon supply chain with this generalised OUT policy achieves over 10% inventory related cost reduction. To enjoy this cost saving, the attitude of first echelon player to cost increases is an essential factor. This attitude also reduces the bullwhip effect. An important insight revealed herein is that a significant amount of benefit comes from the player doing what is the best for the overall supply chain, rather than what is the best for local cost minimisation.     

Optimal hysteresis for a class of deterministic deteriorating two-armed Bandit problem with switching costs

We derive the optimal policy for the dynamic scheduling of a class of deterministic, deteriorating, continuous time and continuous state two-armed Bandit problems with switching costs. Due to the presence of switching costs, the scheduling policy exhibits an hysteretic character. Using this exactly solvable class of models, we are able to explicitly observe the performance of a sub-optimal policy derived from a set of generalized priority indices (generalized Gittins’ indices) similar to those first introduced in a contribution of Asawa and Teneketzis (IEE Trans. Automat. Control 41 (1996) 328).     

How to run biotransformations⿿At the optimal temperature control or isothermally? Mathematical assessment

The optimization of batch biotransformations has attracted attention in recent years because, in the face of growing competition, it is a natural choice for reducing production costs and improving product quality. However, in many cases the effects achieved as a result of optimization may be less valuable in comparison to those obtained when the process is carried out in possibly the simplest way. Hence, in the present paper a mathematical analysis was proposed to assess if application of the optimal temperature control (OTC) in biotransformations with deactivation of native enzyme is justified. At the same time a simple biotransformation process accomplished in the presence of a native enzyme undergoing deactivation independent of or dependent on substrate concentration was considered. The estimation has been done on the basis of the indicator expressed by a quotient of the process duration under time-optimal temperature control and that for isothermal conditions (IC). It has been found that application of the OTC is justified when the biotransformation process is characterized by a high value of the quotient of activation energies referring to enzyme deactivation and for enzymatic reaction which is running up to attain a high conversion and low final enzyme activity. Moreover, application of the OTC in biotransformations with a parallel enzyme deactivation enables significant reduction of process duration in comparison to those with deactivation independent of substrate concentration. Framework proposed here can be helpful for evaluation of economic aspects of the optimally controlled process.     

A study on an inventory model for items with weibull ameliorating

This paper is concerned with the development of ameliorating inventory models. The ameliorating inventory is the inventory of goods whose utility increases over the time by ameliorating activation. The term ameliorating inventory is used in this paper at least, since the terminology is not standard well known. This study is performed according to areas; one is an economic order quantity(EOQ) model for the items whose utility is ameliorating in accordance with Weibull distribution, and the other is a partial selling quantity(PSQ) model developed for selling the surplus inventory accumulated by ameliorating activation. The proposed models cannot be solved directly in a closed form, thus we used a computer program and a graphical solution method to obtain the optimal ordering and selling quantity in this paper. Numerical examples to illustrate the effect of ameliorating rate on inventory polices are shown at the end of this paper.     

Supply chain planning for hurricane response with wind speed information updates

This paper introduces a stochastic inventory control problem that is relevant to proactive disaster recovery planning as it relates to preparing for potential hurricane activity. In particular, we consider a manufacturing or retail organization who experiences demand surge for items such as flashlights, batteries, and gas-powered generators, where the magnitude of demand surge is influenced by various characteristics of an ensuing storm. The planning horizon begins during the initial stages of storm development, when a particular tropical depression or disturbance is first observed, and ends when the storm dissipates. Since hurricane characteristics can be predicted with more accuracy during the later stages of the planning horizon relative to the earlier stages, the inventory control problem is formulated as an optimal stopping problem with Bayesian updates, where the updates are based on hurricane predictions. A dynamic programming algorithm is described to solve the problem, and several examples involving real hurricane wind speed data are presented to illustrate the methodology.     

Optimal partition algorithm of the RBF neural network and its application to financial time series forecasting

A novel neural-network-based method of time series forecasting is presented in this paper. The method combines the optimal partition algorithm (OPA) with the radial basis function (RBF) neural network. OPA for ordered samples is used to perform the clustering for the samples. The centers and widths of the RBF neural network are determined based on the clustering. The difference of the objective functions of the clustering is used to adjust the structure of the neural network dynamically. Thus, the number of the hidden nodes is selected adaptively. The method is applied to stock price prediction. The results of numerical simulations demonstrate the effectiveness of the method. Comparisons with the hard c-means (HCM) algorithm show that the proposed OPA method possesses obvious advantages in the precision of forecasting, generalization, and forecasting trends. Simulations also show that the OPA–orthogonal least squares (OPA–OLS) algorithm, which combines OPA with the OLS algorithm, results in better performance for forecasting trends.     

Heuristic approaches for the inventory-routing problem with backlogging

We study an inventory-routing problem in which multiperiod inventory holding, backlogging, and vehicle routing decisions are to be taken for a set of customers who receive units of a single item from a depot with infinite supply. We consider a case in which the demand at each customer is deterministic and relatively small compared to the vehicle capacity, and the customers are located closely such that a consolidated shipping strategy is appropriate. We develop constructive and improvement heuristics to obtain an approximate solution for this NP-hard problem and demonstrate their effectiveness through computational experiments.     

Determining optimal retail price and lot size under day-terms supplier credit

This paper deals with the problem of determining the retailer's optimal price and lot size simultaneously under the condition of permissible delay in payments. It is assumed that the customer's demand rate is represented by a constant price elasticity function which is a decreasing function of retail price. Investigation of the properties of an optimal solution allows us to develop an algorithm whose validity is illustrated using an example problem. Also, the effect of credit period on the retailer's pricing and lot sizing policy is examined through sensitivity analysis.     

多目的批量过程的受影响批次再调度算法

为解决多目的批量过程调度受延迟扰动的问题,提出了综合考虑新调度质量和稳定性的受影响批次再调度ABR算法,根据状态任务网STN所定义的工艺过程将受到延迟影响的所有批次向后移动最小可能值。仿真算例表明,ARB再调度算法在完成时间指标和开始时间总延迟指标上均优于现有的右移再调度法RSR。     

Optimal operation of batch reactors—a personal view

This paper presents a personal, thus necessarily subjective, view of the operation of batch and semi-batch reactors. The emphasis is on safety, product quality and scale-up. Key characteristics of discontinuous reaction systems are discussed, along with the resulting implications for monitoring, control and optimization. The industrial needs are compared with the research solutions proposed by academia. It is argued that, in industry, measurement and modeling issues are often more important than the algorithmic aspects related to the computation of control and optimization strategies. Major challenges and selected research opportunities are discussed.     

Uncertain probabilities II: the continuous case

We consider probability density functions where some of the parameters are uncertain. We model these uncertainties using fuzzy numbers producing fuzzy probability density functions. In particular, we look at the fuzzy normal, fuzzy uniform, and the fuzzy negative exponential and show how to use them to compute fuzzy probabilities. We also use the fuzzy normal to approximate the fuzzy binomial. Our application is to inventory control (the economic order quantity model) where demand is given by a fuzzy normal probability density.     

基于Intranet的库存管理信息系统的设计与实施

介绍一个基于Ｉｎｔｒａｎｅｔ的库存管理系统的设计与实施,阐述了系统的主要功能、系统结构及软硬件组织和特点。     

Integrated production-inventory models for imperfect production processes under inspection schedules

This paper deals with inventory models that unify the inventory problems of raw materials and finished products for a single product imperfect manufacturing system. The product is manufactured in batches, and raw materials are jointly replenished from outside suppliers. The system is assumed to deteriorate during the production process. As a result, some proportion of defective items is produced. The defective items are reworked at some cost either before or after a sale. Periodic inspections at equally spaced times and restorations of the production process are used to operate the system. The objective is to minimize the expected total cost for the system. A solution procedure is developed to find a near optimal solution for the basic model. The analysis is extended to various cases where the defect rate is a function of the setup cost, the proportion of defective items is not constant, or the inventory system has a limited capacity for raw materials.