Optimal buffer allocation in tandems of last come first served queues

A large fixed number of buffer spaces is given. We consider the problem of allocating these spaces among the nodes of a tandem of last-come-first-served queues with general service time distributions and Poisson external arrivals so as to optimize some performance criterion associated with the time to buffer overflow, such as maximizing its mean or maximizing the probability that it exceeds some value. Consider the following rule of thumb: allocate the buffer spaces in inverse proportion to the logarithms of the effective service rates at the nodes. Here effective service rate denotes the ratio of the service rate to the stationary arrival rate. We prove that this rule of thumb achieves a nearly optimal buffer allocation under the assumption that the service time distributions satisfy an exponential tail condition. This problem has been studied earlier in the context of Jackson networks, where it was shown that the same rule of thumb achieves an allocation that is close to optimal. The technique of proof here is similar, but there are important differences. Both Jackson networks and the LCFS tandems considered here are product form networks (with infinite buffers). Optimism should lead us to expect that the near optimality of this rule of thumb holds much more generally for product-form networks, but this remains a conjecture at present.Research supported by NSF under NCR 8857731, by AT&T, and by Bellcore Inc.Research supported by IBM under a graduate fellowship.     

Demilitarized zone planning: A multiobjective approach

The demilitarized zone has been used frequently as a means to separate conflicting nations. Imposition of a buffer zone free from military activities is considered to be an effective first step to restore peace between hostile nations. The demilitarized zone is usually patrolled by third-party forces to discourage military hostilities. This paper deals with the problem of allocating the third-party supervisory forces in order to assure effective policing of demilitarized zones where there are multiple and conflicting objectives.     

Approximate analysis of unreliable transfer lines with splits in the flow of material

This paper presents a Markov process model and an approximate decomposition technique for a discrete material transfer line with limited buffer capacity. A fraction of the parts processed at some stations in the line may be scrapped or reworked at dedicated machines to meet product quality requirements. Reworked parts are not sent back into the main line. This leads to splits in the flow of material. Processing times are deterministic and identical for all machines and are taken as the time unit. Machine specific times to failure and to repair are geometrically distributed. The model is analyzed through a decomposition into twomachine systems. We develop new decomposition equations for machines performing split operations. Production rates and inventory levels are computed and compared to simulation results. The results indicate that the method produces useful results for a variety of systems.     

软件可靠性指标分配的故障树分析法

首先对目前已有的各种分配技术与方法的特点进行了探讨,介绍了如何采用故障树技术求得导致系统失效的功能模块的最小割集,首次提出将故障树技术运用到可靠性的分配中,创建了可靠性分配的故障树快速分配模型并具体分析了其在软件可靠性指标分配中的应用． 最后,分析了这种技术的不足,并对该方法可能的改进进行了一些探讨．     

Proposal of Rip up & Re allocate Algorithm for Optical Layer 2 Switch Network

We are developing an optical layer-2s witch network that uses both wavelength-division multiplexing and time-division multiplexing technologies for efficient traffic aggregation in metro networks.For efficient traffic aggregation,path bandwidth control is key because it strongly affects bandwidth efficiency.For this paper,we propose a dynamic time-slot allocation method that uses periodic information of difference values of traffic variation.This method can derive near-optimal allocation with lower computational cost,which enlarges the maximum available network size compared with conventional time-slot allocation methods.Numerical results show that the proposed method enables dynamic path control in 1K-node-scale optical layer-2s witch network,which leads to cost-effective metro networks.     

The effect of physical back-diffusion of 13CO2 tracer on the coupling between photosynthesis and soil CO2 efflux in grassland

Pulse labelling experiments provide a common tool to study short-term processes in the plant–soil system and investigate below-ground carbon allocation as well as the coupling of soil CO₂ efflux to photosynthesis. During the first hours after pulse labelling, the measured isotopic signal of soil CO₂ efflux is a combination of both physical tracer diffusion into and out of the soil as well as biological tracer release via root and microbial respiration. Neglecting physical back-diffusion can lead to misinterpretation regarding time lags between photosynthesis and soil CO₂ efflux in grassland or any ecosystem type where the above-ground plant parts cannot be labelled in gas-tight chambers separated from the soil. We studied the effects of physical ¹³CO₂ tracer back-diffusion in pulse labelling experiments in grassland, focusing on the isotopic signature of soil CO₂ efflux. Having accounted for back-diffusion, the estimated time lag for first tracer appearance in soil CO₂ efflux changed from 0 to 1.81±0.56 h (mean±SD) and the time lag for maximum tracer appearance from 2.67±0.39 to 9.63±3.32 h (mean±SD). Thus, time lags were considerably longer when physical tracer diffusion was considered. Using these time lags after accounting for physical back-diffusion, high nocturnal soil CO₂ efflux rates could be related to daytime rates of gross primary productivity (R²=0.84). Moreover, pronounced diurnal patterns in the δ¹³C of soil CO₂ efflux were found during the decline of the tracer over 3 weeks. Possible mechanisms include diurnal changes in the relative contributions of autotrophic and heterotrophic soil respiration as well as their respective δ¹³C values. Thus, after accounting for physical back-diffusion, we were able to quantify biological time lags in the coupling of photosynthesis and soil CO₂ efflux in grassland at the diurnal time scale.     

Optimizing inventory decisions in a two-level supply chain with order quantity constraints

A fundamental assumption in traditional inventory models is that all of the ordered items are of perfect quality. A two-level supply chain is considered consists of one retailer and a collection of suppliers that operate within a finite planning horizon, including multiple periods, and a model is formulated that simultaneously determines both supplier selection and inventory allocation problems in the supply chain. It is supposed that the ordered products dependent on the suppliers include a certain percentage of imperfect quality products and have different prices. In this paper, we study the impact of the retailer’s financial constraint. On the other hand, suppliers have restricted capacities and set minimum order quantity (MOQ) policy for the retailer’s order amount happened in each period. So, the problem is modeled as a mixed integer nonlinear programming. The purpose of this model is to maximize the total profit. The nutrients, fishery and fruitage industries give good examples for the proposed model. A numerical example is presented to indicate the efficiency of the proposed model. Considering the complexity of the model, a genetic algorithm (GA) is presented to solve the model. We demonstrate analytically that the proposed genetic algorithm is suitable in the feasible situations.     

Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal

Container terminals pay more and more attention to the service quality of inland transport modes such as tucks, trains and barges. Truck appointment systems are a common approach to reduce truck turnaround times. This paper provides a tool to use the truck appointment system to increase not only the service quality of trucks, but also of trains, barges and vessels. We propose a mixed integer linear programming model to determine the number of appointments to offer with regard to the overall workload and the available handling capacity. The model is based on a network flow representation of the terminal and aims to minimize overall delays at the terminal. It simultaneously determines the number of truck appointments to offer and allocates straddle carriers to different transport modes. Numerical experiments, conducted on actual data, quantify the benefits of this combined solution approach. Discrete-event simulation validates the results obtained by the optimization model in a stochastic environment.     

Optimal two-phase vaccine allocation to geographically different regions under uncertainty

In this article, we consider a decision process in which vaccination is performed in two phases to contain the outbreak of an infectious disease in a set of geographic regions. In the first phase, a limited number of vaccine doses are allocated to each region; in the second phase, additional doses may be allocated to regions in which the epidemic has not been contained. We develop a simulation model to capture the epidemic dynamics in each region for different vaccination levels. We formulate the vaccine allocation problem as a two-stage stochastic linear program (2-SLP) and use the special problem structure to reduce it to a linear program with a similar size to that of the first stage problem. We also present a Newsvendor model formulation of the problem which provides a closed form solution for the optimal allocation. We construct test cases motivated by vaccine planning for seasonal influenza in the state of North Carolina. Using the 2-SLP formulation, we estimate the value of the stochastic solution and the expected value of perfect information. We also propose and test an easy to implement heuristic for vaccine allocation. We show that our proposed two-phase vaccination policy potentially results in a lower attack rate and a considerable saving in vaccine production and administration cost.