Elementary methods for an occupancy problem of storage

Summary This paper considers the probabilities of first emptiness in two storage systems. The first, an infinite dam in discrete time, is fed by inputs whose distribution is geometric in unit time-intervals; at the end of each of these, there occurs a unit release. The second is an infinite dam in continuous time with Poisson inputs, for which the release occurs at constant unit rate except when the dam is empty.First emptiness in both dams may be formulated as a special type of classical occupancy problem. The probabilities of emptiness are derived by direct elementary methods, and their generating functions found. These are shown to define proper distributions only if the mean input per unit time does not exceed the corresponding release.     

On dams with continuous semi-Markovian inputs

An infinite capacity dam subject to semi-Markovian inputs and a content dependent release rule will be discussed. The content process will be constructed, the distributions of the content at time t and time to first emptiness will be computed, and the limiting distribution of the content process will be obtained in a special case. Our methods rely heavily on Markov renewal theory with continuous state spaces.     

Stochastic Models for the Amount of Overflow in a Finite Dam with Random Inputs,Random Outputs,and Exponential Release Policy

In this article, we discuss finite dam models to study the expected amount of overflow in a given time. The inputs into the dam are taken as random and there are two types of outputs—one is random and the other is deterministic which is proportional to the content of the dam. The master equation for the expected amount of overflow is an one dimensional equation with separable kernel. For this class of master equation, the integral equation for the expected amount of overflow has been transformed exactly into ordinary differential equation with variable coefficients. The imbedding method is used to study the expected amount of overflow in a given time without emptiness in this period. We also consider the model for the expected amount of overflow in a given time with any number of emptiness of the dam in this period. The results are derived in the form of a third order differential Equation for the Laplace transformation function for the expected overflow. The closed form analytical solutions are obtained in terms of beta functions and degenerate hyper-geometric functions of two variables.     

Finite dams with double level of release

We considered a finite dam with discrete additive input and double level of release. If the current dam content is not greater than a certain boundM, the release is one unit unless the dam is empty; and if the current dam content is greater thanM, the release isr (? 1) units provided it is available, otherwise the whole content will be withdrawn. We derive all the expressions of the distributions of first emptiness with and without overflow, the distributions of emptiness with and without overflow, the time dependent distributions of dam content with and without overflow, and the distributions of overflow times and quantities. IfM is equal to the dam capacity, the results are reduced to the case of unit release; and ifM=0, the results are reduced to the case of releaser.     

Emptiness formation probability of XX-chain in diffusion process

We study the distribution of emptiness formation probability of XX-model in the diffusion process. There exits a Gaussian decay as well as an exponential decay. The Gaussian decay is caused by the existence of zero point in the Fermi distribution function. The correlation length for each point of scaling factor varies up to the initial condition, monotonically or non-monotonically.     

Storage problems in continuous time with random inputs,random outputs,and deterministic release

The subject of study here is the model of a dam, with random inputs and outputs along with a deterministic release. The amounts of the Poisson jumps, either up or down, are independently and identically distributed. Closed form solutions are obtained for the Laplace transforms of first passage densities to different situations of overflow or emptiness. These results can throw insights regarding different threshold studies in storage, inventory, biological, and environmental problems. The closed form solutions are obtained by applying imbedding methods for different types of densities conceptualized in novel ways.     

Stochastic Dynamics for Passage Times and Diffusion Approximations for Finite Capacity Storage Models with Different Kinds of Barriers

In this article, we discuss a number of storage models of finite capacity with random inputs, random outputs, and linear release policy. They form a class of one-dimensional master equations with separable kernels. For this class of problems, the integral equations for first overflow or first emptiness can be transformed exactly into ordinary differential equations. Analysis is done with separable kernel. For all the stochastic models, two barriers are considered: one at X = 0 and the other at X = k, and the barriers are treated as absorbing or reflecting. The imbedding method is used to derive a third order differential equation. We consider first passage times for overflow without or with emptiness of the dam. We also study the passage times for first emptiness with and without overflows. The expected amount of overflows in a given time is also calculated. Finally, by suitable statistical features, all these models are converted into diffusion process with drift. Closed form solutions are obtained for all the problems in terms of Laplace transform functions. For the diffusion process with drift first passage time density is arrived at by treating X = 0 and X = k as absorbing barriers. One of the barriers as reflecting is also studied.     

Perishable Inventory System at Service Facilities with N Policy

Abstract

This article presents a perishable stochastic inventory system under continuous review at a service facility in which the waiting hall for customers is of finite size M. The service starts only when the customer level reaches N (< M), once the server has become idle for want of customers. The maximum storage capacity is fixed as S. It is assumed that demand for the commodity is of unit size. The arrivals of customers to the service station form a Poisson process with parameter λ. The individual customer is issued a demanded item after a random service time, which is distributed as negative exponential. The items of inventory have exponential life times. It is also assumed that lead time for the reorders is distributed as exponential and is independent of the service time distribution. The demands that occur during stock out periods are lost.The joint probability distribution of the number of customers in the system and the inventory levels is obtained in steady state case. Some measures of system performance in the steady state are derived. The results are illustrated with numerical examples.     

On stochastic processes in a multilevel control bulk queueing system

This article analyzes some stochastic processes that arise in a bulk single server queue with continuously operating server, state dependent compound Poisson input flow and general state dependent service process. The authors treat the queueing process as a semi–regenerative process and obtain the invariant probability measure and the transient distribution for the embedded Markov chain. The stationary probability measure for the queueing process with continuous time parameter is found by using semi-regenerative techniques. The authors also study the input and output processes and establish ergodic theorems for some functionals of these processes. The results are obtained in terms of the invariant probability measure for the embedded process and the stationary measure for the queueing process with continuous time parameter     

Finite time ruin probabilities for tempered stable insurance risk processes

We study the probability of ruin before time t$t$ for the family of tempered stable Lévy insurance risk processes, which includes the spectrally positive inverse Gaussian processes. Numerical approximations of the ruin time distribution are derived via the Laplace transform of the asymptotic ruin time distribution, for which we have an explicit expression. These are benchmarked against simulations based on importance sampling using stable processes. Theoretical consequences of the asymptotic formulae indicate that some care is needed in the choice of parameters to avoid exponential growth (in time) of the ruin probabilities in these models. This, in particular, applies to the inverse Gaussian process when the safety loading is less than one.     

The MMCPP/GE/c Queue

We obtain the queue length probability distribution at equilibrium for a multi-server, single queue with generalised exponential (GE) service time distribution and a Markov modulated compound Poisson arrival process (MMCPP) – i.e., a Poisson point process with bulk arrivals having geometrically distributed batch size whose parameters are modulated by a Markovian arrival phase process. This arrival process has been considered appropriate in ATM networks and the GE service times provide greater flexibility than the more conventionally assumed exponential distribution. The result is exact and is derived, for both infinite and finite capacity queues, using the method of spectral expansion applied to the two dimensional (queue length by phase of the arrival process) Markov process that describes the dynamics of the system. The Laplace transform of the interdeparture time probability density function is then obtained. The analysis therefore could provide the basis of a building block for modelling networks of switching nodes in terms of their internal arrival processes, which may be both correlated and bursty.     

A brownian motion model of return migration

This paper considers a continuous time, continuous state stochastic process to determine a theoretical model and empirical parameters for the probability distribution of remigration. A Brownian motion model is used for simplicity, with empirical findings drawn from a study of Israeli return migrants. A negative relationship between remigration (sojourn) time and the probability of return time is used to provide forecasts of remigration which can help governments who seek actively the return of their migrants to reach better decisions regarding the timing of their efforts.     

On Several Two-Boundary Problems for a Particular Class of Lévy Processes

Several two-boundary problems are solved for a special Lévy process: the Poisson process with an exponential component. The jumps of this process are controlled by a homogeneous Poisson process, the positive jump size distribution is arbitrary, while the distribution of the negative jumps is exponential. Closed form expressions are obtained for the integral transforms of the joint distribution of the first exit time from an interval and the value of the overshoot through boundaries at the first exit time. Also the joint distribution of the first entry time into the interval and the value of the process at this time instant are determined in terms of integral transforms.     

On the Decay Rates of Buffers in Continuous Flow Lines

Consider a tandem system of machines separated by infinitely large buffers. The machines process a continuous flow of products, possibly at different speeds. The life and repair times of the machines are assumed to be exponential. We claim that the overflow probability of each buffer has an exponential decay, and provide an algorithm to determine the exact decay rates in terms of the speeds and the failure and repair rates of the machines. These decay rates provide useful qualitative insight into the behavior of the flow line. In the derivation of the algorithm we use the theory of Large Deviations.     

Inventory control with the gamma probability distribution

Application of inventory theory often rely on the normal and negative exponential distributions to represent the lead time demand of fast and slow moving items respectively. Yet it is now accepted that both distributions, when taken together, are incapable of adequately describing the demand characteristics of all items found in the typical inventory. Instead there has been a growing interest in the use of the gamma probability distribution because it not only encompasses both former distributions as special cases but also covers the gaps left by them. In the process a number of methods for calculating control parameters have appeared in the literature for items with gamma distributed lead time demand. As knowledge about the problem has increased there has been a general tendency towards greater simplification. This paper continues the trend by introducing an approach that depends only on concepts from basic statistics. The aim is to eliminate unnecessary complexity and make the associated theory easier to understand.     

一类马氏环境中连续型传染病模型的灭绝概率

这篇文章主要研究一类马氏环境中的连续型传染病模型,即假设疾病传染率和病人减少(死亡或治愈)的发生频率及数目都受一外在马氏过程的影响.在这些假设下,我们得出初始状态为i时疾病的灭绝概率满足的积分方程,并通过Laplace-变换的方法,给出了积分方程的解.进一步,当外在马氏环境为两个状态,并且每次病人减少的数目都服从指数分布时,给出了灭绝概率Laplace-变换的明确表达式.     

Quasi-stationary distributions and Yaglom limits of self-similar Markov processes

We discuss the existence and characterization of quasi-stationary distributions and Yaglom limits of self-similar Markov processes that reach 0 in finite time. By Yaglom limit, we mean the existence of a deterministic function g$g$ and a non-trivial probability measure ν$\nu$ such that the process rescaled by g$g$ and conditioned on non-extinction converges in distribution towards ν$\nu$. We will see that a Yaglom limit exists if and only if the extinction time at 0$0$ of the process is in the domain of attraction of an extreme law and we will then treat separately three cases, according to whether the extinction time is in the domain of attraction of a Gumbel, Weibull or Fréchet law. In each of these cases, necessary and sufficient conditions on the parameters of the underlying Lévy process are given for the extinction time to be in the required domain of attraction. The limit of the process conditioned to be positive is then characterized by a multiplicative equation which is connected to a factorization of the exponential distribution in the Gumbel case, a factorization of a Beta distribution in the Weibull case and a factorization of a Pareto distribution in the Fréchet case.     

On the lifetime behavior of a discrete time shock model

In this article, we study a shock model in which the shocks occur according to a binomial process, i.e. the interarrival times between successive shocks follow a geometric distribution with mean 1/p$1/p$. According to the model, the system fails when the time between two consecutive shocks is less than a prespecified level. This is the discrete time version of the so-called δ$\delta$-shock model which has been previously studied for the continuous case. We obtain the probability mass function and probability generating function of the system’s lifetime. We also present an extension of the results to the case where the shock occurrences are dependent in a Markovian fashion.     

On the exact distribution and mean value function of a geometric process with exponential interarrival times

The geometric process is considered when the distribution of the first interarrival time is assumed to be exponential. An analytical expression for the one dimensional probability distribution of this process is obtained as a solution to a system of recursive differential equations. A power series expansion is derived for the geometric renewal function by using an integral equation and evaluated in a computational perspective. Further, an extension is provided for the power series expansion of the geometric renewal function in the case of the Weibull distribution.     

Analysis of a dynamic assignment of impatient customers to parallel queues

Consider a number of parallel queues, each with an arbitrary capacity and multiple identical exponential servers. The service discipline in each queue is first-come-first-served (FCFS). Customers arrive according to a state-dependent Poisson process. Upon arrival, a customer joins a queue according to a state-dependent policy or leaves the system immediately if it is full. No jockeying among queues is allowed. An incoming customer to a parallel queue has a general patience time dependent on that queue after which he/she must depart from the system immediately. Parallel queues are of two types: type 1, wherein the impatience mechanism acts on the waiting time; or type 2, a single server queue wherein the impatience acts on the sojourn time. We prove a key result, namely, that the state process of the system in the long run converges in distribution to a well-defined Markov process. Closed-form solutions for the probability density function of the virtual waiting time of a queue of type 1 or the offered sojourn time of a queue of type 2 in a given state are derived which are, interestingly, found to depend only on the local state of the queue. The efficacy of the approach is illustrated by some numerical examples.