An inventory sharing and allocation method for a multi-location service parts logistics network with time-based service levels

We consider a model to allocate stock levels at warehouses in a service parts logistics network. The network is a two-echelon distribution system with one central warehouse with infinite capacity and a number of local warehouses, each facing Poisson demands from geographically dispersed customers. Each local warehouse uses a potentially different base stock policy. The warehouses are collectively required to satisfy time-based service targets: Certain percentages of overall demand need to be satisfied from facilities within specified time windows. These service levels not only depend on the distance between customers and the warehouses, but also depend on the part availabilities at the warehouses. Moreover, the warehouses share their inventory as a way to increase achieved service levels, i.e., when a local warehouse is out of stock, demand is satisfied with an emergency shipment from another close-by warehouse. Observing that the problem of finding minimum-cost stock levels is an integer non-linear program, we develop an implicit enumeration-based method which adapts an existing inventory sharing model from the literature, prioritizes the warehouses for emergency shipments, and makes use of a lower bound. The results show that the proposed inventory sharing strategy results in considerable cost reduction when compared to the no-sharing case and the method is quite efficient for the considered test problems.     

Issues in the use of ratings-based versus choice-based conjoint analysis in operations management research

Conjoint analysis has played an important role in helping make a number of operations management decisions including product and service design, supplier selection, and service operations capacity. Many recent advances in this area have raised questions about the most appropriate form of conjoint analysis for this research. We review recent developments in the literature and provide new evidence on how the choice between ratings- and choice-based conjoint models might affect the estimates of customer demand used in operations management models.     

Calculation of delay characteristics for multiserver queues with constant service times

We consider a discrete-time infinite-capacity queueing system with a general uncorrelated arrival process, constant-length service times of multiple slots, multiple servers and a first-come-first-served queueing discipline. Under the assumption that the queueing system can reach a steady state, we first establish a relationship between the steady-state probability distributions of the system content and the customer delay. Next, by means of this relationship, an explicit expression for the probability generating function of the customer delay is obtained from the known generating function of the system content, derived in previous work. In addition, several characteristics of the customer delay, namely the mean value, the variance and the tail distribution of the delay, are derived through some mathematical manipulations. The analysis is illustrated by means of some numerical examples.     

基于可拓策略生成技术的商品搜索服务改进研究

购买者在使用商品搜索服务时所得搜索结果数量不符合其主观要求是一个典型而普遍的矛盾问题.在分析矛盾问题的基础上,提出以可拓策略生成技术改进商品搜索服务的方法.该方法通过对购买者提出的搜索要求进行发散分析及相关分析,以形成各种可能变换,并依据关联函数寻求问题的解变换,以及利用评价函数对解变换进行优选.给出了关于策略生成的基本算法,并实现于笔记本电脑导购网站平台上.实验及测试结果表明,系统能有效生成矛盾问题的解变换,从而改进了搜索服务的质量.     

Ordinal Optimization of G/G/1/K Polling Systems with <Emphasis Type="Italic">k</Emphasis>-Limited Service Discipline

In this paper, we propose an ordinal optimization theory based algorithm to solve the optimization problem of G/G/1/K polling system with k-limited service discipline for a good enough solution using limited computation time. We assume that the arrival rates do not deteriorate visibly within a very short period. Our approach consists of two stages. In the first stage, we employ a typical genetic algorithm to select N=1024 roughly good solutions from the huge discrete solution space Ω using an offline trained artificial neural network as a surrogate model for fitness evaluation. The second stage consists of several substages to select estimated good enough solutions from the previous N, and the solution obtained in the last substage is the good enough solution that we seek. Using numerous tests, we demonstrate: (i) the computational efficiency of our algorithm in the aspect that we can apply our algorithm in real-time based on the arrival rate assumption; (ii) the superiority of the good enough solution, which achieves drastic objective value reduction in comparison with other existing service disciplines. We provide a performance analysis for our algorithm based on the derived models. The results show that the good enough solution that we obtained is among the best 3.31×10⁻⁶% in the solution space with probability 0.99. This research work was supported in part by the National Science Council of Taiwan, ROC, Grant NSC95-2221-E-009-099-MY2.     

Perturbation analysis of an <Emphasis Type="Italic">M</Emphasis>/<Emphasis Type="Italic">M</Emphasis>/1 queue in a diffusion random environment

We study in this paper an M/M/1 queue whose server rate depends upon the state of an independent Ornstein–Uhlenbeck diffusion process (X(t)) so that its value at time t is μ φ(X(t)), where φ(x) is some bounded function and μ>0. We first establish the differential system for the conditional probability density functions of the couple (L(t),X(t)) in the stationary regime, where L(t) is the number of customers in the system at time t. By assuming that φ(x) is defined by φ(x)=1−ε((x ∧ a/ε)∨(−b/ε)) for some positive real numbers a, b and ε, we show that the above differential system has a unique solution under some condition on a and b. We then show that this solution is close, in some appropriate sense, to the solution to the differential system obtained when φ is replaced with Φ(x)=1−ε x for sufficiently small ε. We finally perform a perturbation analysis of this latter solution for small ε. This allows us to check at the first order the validity of the so-called reduced service rate approximation, stating that everything happens as if the server rate were constant and equal to .      

Optimal control for linear discrete-time systems with Markov perturbations in Hilbert spaces

Email: vio{at}utgjiu.ro Received on September 12, 2007; Accepted on December 26, 2008 In this article, we discuss a quadratic control problem forlinear discrete-time systems with Markov perturbations in Hilbertspaces, which is linked to a discrete-time Riccati equationdefined on certain infinite-dimensional ordered Banach space.We prove that under stabilizability and stochastic uniform observabilityconditions, the Riccati equation has a unique, uniformly positive,bounded on N and stabilizing solution. Based on this result,we solve the proposed optimal control problem. An example illustratesthe theory.     

On the BMAP/G/1 G-queues with second optional service and multiple vacations

This paper deals with an BMAP/G/1 G-queues with second optional service and multiple vacations. Arrivals of positive customers and negative customers follow a batch Markovian arrival process (BMAP) and Markovian arrival process (MAP), respectively. After completion of the essential service of a customer, it may go for a second phase of service. The arrival of a negative customer removes the customer being in service. The server leaves for a vacation as soon as the system empties and is allowed to take repeated (multiple) vacations. By using the supplementary variables method and the censoring technique, we obtain the queue length distributions. We obtain the mean of the busy period based on the renewal theory.     

A four-input three-stage queuing network approach to model an industrial system

An industrial system is represented as a four-input, three-stage queuing network in this paper. The four-input queuing network receives orders from clients, and the orders are waiting to be served. Each order comprises (i) time of occurrence of the orders, and (ii) quantity of items to be delivered in each order. The objective of this paper is to compute the optimal path which produces the least response time for the delivery of items to the final destination along the three stages of the network. The average number of items that can be delivered with this minimum response time constitute the optimum capacity of the queuing network. After getting serviced by the last node (a queue and its server) in each stage of the queuing network, a decision is made to route the items to the appropriate node in the next stage which can produce the least response time. Performance measures such as average queue lengths, average response times, average waiting times of the jobs in the four-input network are derived and plotted. Closed-form expressions for the equivalent service rate, equivalent average queue lengths, equivalent response and waiting times of a single equivalent queue with a server representing the entire four-input queuing network are also derived and plotted.     

民机数字化运营支持研究与方案设计

数字化运营支持是未来民机客户服务市场竞争的核心因素。未来民机型号的成功,不仅需要飞机设计于与制造的成功,更需要可持续数字化运营支持技术的成功。基于大数据分析的云端交付模式与信息安全防护体系,构建数字航空环境提供“智能服务”,搭建适合国产民机的数字化运营支持体系,保障国产民机商业成功。本文概述了数字化运营支持技术,总结出其定量化、实时化、综合化、智能化的特点。民机数字化运营支持以先进信息技术为基础,为航空公司提供数据分析、知识关联、智能辅助工具及预见性软件应用,变革运营信息的收集、传输与利用模式,从而不断提高民机安全性、可靠性、经济性与环保性。数字化运营支持是当前国际民机客户服务领域重要的技术手段与商业模式,更是未来民机客服的发展方向。