Strong stability of the embedded Markov chain in an GI/M/1 queue with negative customers

This paper is devoted to the investigation for sufficient conditions of the strong stability of the embedded Markov chain in GI/M/1 queueing system with negative customers. After perturbing the occurrence rate of the negative customers, we prove the strong stability of the considered Markov chain with respect to a convenient weight variation norm. Furthermore, we estimate the deviation of its transition operators and provide an upper bound to the approximation error. This results allow us to understand how the negative customers will affect the system’s level of performance.     

Acyclic dominating partitions

Given a graph G=(V, E), let ${\mathcal{P}}$ be a partition of V. We say that ${\mathcal{P}}$ is dominating if, for each part P of ${\mathcal{P}}$, the set V\P is a dominating set in G (equivalently, if every vertex has a neighbor of a different part from its own). We say that ${\mathcal{P}}$ is acyclic if for any parts P, P′ of ${\mathcal{P}}$, the bipartite subgraph G[P, P′] consisting of the edges between P and P′ in ${\mathcal{P}}$ contains no cycles. The acyclic dominating number ad(G) of G is the least number of parts in any partition of V that is both acyclic and dominating; and we shall denote by ad(d) the maximum over all graphs G of maximum degree at most d of ad(G). In this article, we prove that ad(3)=2, which establishes a conjecture of P. Boiron, É. Sopena, and L. Vignal, DIMACS/DIMATIA Conference “Contemporary Trends in Discrete Mathematics”, 1997, pp. 1–10. For general d, we prove the upper bound ad(d)=O(dlnd) and a lower bound of ad(d)=Ω(d). © 2009 Wiley Periodicals, Inc. J Graph Theory 64: 292–311, 2010     

A model for real-time failure prognosis based on hidden Markov model and belief rule base

As one of most important aspects of condition-based maintenance (CBM), failure prognosis has attracted an increasing attention with the growing demand for higher operational efficiency and safety in industrial systems. Currently there are no effective methods which can predict a hidden failure of a system real-time when there exist influences from the changes of environmental factors and there is no such an accurate mathematical model for the system prognosis due to its intrinsic complexity and operating in potentially uncertain environment. Therefore, this paper focuses on developing a new hidden Markov model (HMM) based method which can deal with the problem. Although an accurate model between environmental factors and a failure process is difficult to obtain, some expert knowledge can be collected and represented by a belief rule base (BRB) which is an expert system in fact. As such, combining the HMM with the BRB, a new prognosis model is proposed to predict the hidden failure real-time even when there are influences from the changes of environmental factors. In the proposed model, the HMM is used to capture the relationships between the hidden failure and monitored observations of a system. The BRB is used to model the relationships between the environmental factors and the transition probabilities among the hidden states of the system including the hidden failure, which is the main contribution of this paper. Moreover, a recursive algorithm for online updating the prognosis model is developed. An experimental case study is examined to demonstrate the implementation and potential applications of the proposed real-time failure prognosis method.     

Developing a market-based approach to managing the US strategic petroleum reserve

The Strategic Petroleum Reserve has not been used effectively to manage the consequences of oil shocks in the United States. The main reason is that political decision makers tend to hoard the reserves during crises and bureaucratic processes delay the sale of the reserves. Also, the enabling legislation focused on ameliorating shortages whereas disruptions result price spikes rather than shortages. We develop a Markov game of the buildup and drawdown of the reserve in which a public player aims to maximize consumer welfare at the same time private holders of inventory maximize their profit. The methodological contribution in this paper is the development of financial options to implement the public player’s optimal policy. We use the solution of this game to calculate the number and value of options necessary for the private marketplace to trigger the optimal buildup and drawdown of the reserve.     

Optimally maintaining a Markovian deteriorating system with limited imperfect repairs

We consider the problem of optimally maintaining a periodically inspected system that deteriorates according to a discrete-time Markov process and has a limit on the number of repairs that can be performed before it must be replaced. After each inspection, a decision maker must decide whether to repair the system, replace it with a new one, or leave it operating until the next inspection, where each repair makes the system more susceptible to future deterioration. If the system is found to be failed at an inspection, then it must be either repaired or replaced with a new one at an additional penalty cost. The objective is to minimize the total expected discounted cost due to operation, inspection, maintenance, replacement and failure. We formulate an infinite-horizon Markov decision process model and derive key structural properties of the resulting optimal cost function that are sufficient to establish the existence of an optimal threshold-type policy with respect to the system’s deterioration level and cumulative number of repairs. We also explore the sensitivity of the optimal policy to inspection, repair and replacement costs. Numerical examples are presented to illustrate the structure and the sensitivity of the optimal policy.     

Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi’s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is non-conforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure.     

Managing an integrated production inventory system with information on the production and demand status and multiple non-unitary demand classes

In this paper, we study a system consisting of a manufacturer or supplier serving several retailers or clients. The manufacturer produces a standard product in a make-to-stock fashion in anticipation of orders emanating from n retailers with different contractual agreements hence ranked/prioritized according to their importance. Orders from the retailers are non-unitary and have sizes that follow a discrete distribution. The total production time is assumed to follow a k₀-Erlang distribution. Order inter-arrival time for class l demand is assumed to follow a k_l-Erlang distribution. Work-in-process as well as the finished product incur a, per unit per unit of time, carrying cost. Unsatisfied units from an order from a particular demand class are assumed lost and incur a class specific lost sale cost. The objective is to determine the optimal production and inventory allocation policies so as to minimize the expected total (discounted or average) cost. We formulate the problem as a Markov decision process and show that the optimal production policy is of the base-stock type with base-stock levels non-decreasing in the demand stages. We also show that the optimal inventory allocation policy is a rationing policy with rationing levels non-decreasing in the demand stages. We also study several important special cases and provide, through numerical experiments, managerial insights including the effect of the different sources of variability on the operating cost and the benefits of such contracts as Vendor Managed Inventory or Collaborative Planning, Forecasting, and Replenishment. Also, we show that a heuristic that ignores the dependence of the base-stock and rationing levels on the demands stages can perform very poorly compared to the optimal policy.     

有优先权且有两不同修理设备的两部件冷贮备可修系统的可靠性分析

在开关不完全可靠的情况下,研究了两个不同型部件和两个修理设备组成的冷贮备系统.在部件1有工作和修理优先权的条件下,建立了在部件和开关工作寿命及修理时间均服从指数分布的可修系统模型,利用Markov理论和Laplace变换,给出了系统可靠度的Laplace表达式及系统的稳态指标.     

马尔柯夫链在多介质环境归趋研究中的应用

以开放的环境系统为依托,阐述了马尔柯夫理论在多介质环境归趋研究中的科学性与合理性,并结合国家重点课题—黄河兰州段典型污染物迁移/转化特性及承纳水平研究,研究壬基酚聚氧乙烯醚(nonylphenol polyethoxylates—NPEOs)在黄河兰州段的环境归趋.研究结果表明,利用马尔柯夫模型可以确定污染物在环境介质间的迁移时间、环境介质内的滞留时间、任意时刻污染物在不同环境介质内的含量、给定时间内不同迁移转化过程的迁移量和降解量、环境系统达到稳定的时间、污染物在环境系统内的稳定分布、以及污染物的环境容量或排放标准.     

On general Bernstein and Nikol’ski type inequalities

The goal of this paper is to establish the relations between general Bernstein and Nikol’ski type inequalities under some weak conditions. From these relations some known classical inequalities are implied. Also, a family of functions equipped with Bernstein type inequality which satisfies Nikol’ski type inequality is found.