Time-dependent performance approximation of truck handling operations at an air cargo terminal

This paper provides an analytical solution for the time-dependent performance evaluation of truck handling operations at an air cargo terminal. The demand for loading and unloading operations is highly time-dependent and stochastic for two classes of trucks. Two heterogeneous handling facilities with multiple servers are available to handle trucks assuming exponentially distributed processing times. Trucks are routed to a handling facility depending on the current state of the system upon arrival. To approximate the time-dependent behavior of such heterogeneous queueing systems, we develop a stationary backlog-carryover (SBC) approach. A numerical study compares this approach with simulations and demonstrates its applicability to real-world input data.     

Discrete-time queues with generally distributed service times and renewal-type server interruptions

In this contribution, we investigate a discrete-time single-server queue subjected to server interruptions. Server interruptions are modeled as an on/off process with geometrically distributed on-periods and generally distributed off-periods. As message lengths can exceed one time-slot, different operation modes are considered, depending on whether service of an interrupted message continues, partially restarts or completely restarts after an interruption. For all alternatives, we establish expressions for the steady-state probability generating functions (pgf) of the buffer contents at message departure times and random slot boundaries, of the unfinished work at random slot boundaries, the message delay, and the lengths of the idle and busy periods. From these results, closed-form expressions for various performance measures, such as mean and variance of the buffer occupancy and message delay, can be established. As an application, we show that this model is able to assess performance of a multi-class priority scheduling system. We then illustrate our approach with some numerical examples.     

A simulation modeling and analysis for RFID-enabled mixed-product loading strategy for outbound logistics: A case study

Loading of trucks in a plant can be a problem when different kinds of products are to be loaded on the same truck, but these goods are not ready. Therefore, the truck has to wait at the loading bay for an unbearably long time, blocking other trucks also in the process. In this paper we address this problem and present several alternative strategies for drawing loading schedules in such situations, using information on status of products obtained with radio-frequency identification (RFID) technology, and compare their performance with traditional strategies, without RFID. A case study on a giant printing and paper bag manufacturer is conducted. Simulation models under these strategies are built for comparisons with respect to three performance measures: average operating time in system, throughput of trucks and percentage of tardy performance trucks. Results demonstrate that these strategies have different performances with respect to different criteria.     

Analyzing the Trade-off Between Investing in Service Channels and Satisfying the Targeted User Service for Brazilian Internet Service Providers

The computer connection to the Internet is provided by firms known as internet service providers (ISPs). The simplest mode of physical connection is when the user connects to an ISP's service channel by an ordinary telephone line (dial-up). Finding an available channel may not be an easy task, especially during the peak hours of many Brazilian ISPs. This results in a problem for the ISPs, which is how to achieve the most appropriate trade-off between investing in capacity and satisfying the target user service level. This paper analyzes this trade-off based on a three-step approach: (i) determine user arrival and service processes in chosen periods, (ii) select an appropriate queueing model using some simplifying assumptions, and (iii) generate trade-off curves between system performance measures. To illustrate the application of this approach, some results derived from a case study performed at an ISP in Sao Paulo state are given.     

Meta-heuristics implementation for scheduling of trucks in a cross-docking system with temporary storage

Cross-docking is an approach in inventory management which can reduce inventories, lead times and customer response time. In this strategy, products and shipments are unloaded from inbound trucks, sorted and categorized based on their characteristics, moved and loaded onto outbound trucks for delivery to demand points in a distribution network. The important fact is that, the items are stored in the inventory for a period which is primarily less than the actual time allocated to keep these items in a typical warehouse. Therefore, total cost and space requirement for inventory can be cut down. One of the most important targets in such systems is to establish coordination between the performance of inbound and outbound trucks in that these trucks can be scheduled, and the product items can be allocated to trucks effectively. This paper addresses some meta-heuristics to find the best sequence of inbound and outbound trucks, so that the objective, minimizing the total operation time called makespan, can be satisfied. Furthermore, not only the efficiency and capability of the algorithms’ parameters are assessed and analyzed by some performance measures, but also these meta-heuristics are compared with each other in order to find out the set of homogeneous algorithms among all proposed algorithms. By this analysis, it can be shown that the suitability of these meta-heuristics is quite sensible especially for the cross-docking systems with large sizes in which a high volume of inbound or outbound trucks transmit the product items.     

Ordinal optimization of DEDS

In this paper we argue thatordinal rather thancardinal optimization, i.e., concentrating on finding good, better, or best designs rather than on estimating accurately the performance value of these designs, offers a new, efficient, and complementary approach to the performance optimization of systems. Some experimental and analytical evidence is offered to substantiate this claim. The main purpose of the paper is to call attention to a novel and promising approach to system optimization.This work is supported by NSF grants CDR-88-03012, DDM-89-14277, ONR contracts N00014-90-J-1093, N00014-89-J-1023, and army contracts DAAL-03-83-K-0171, DAAL-91-G-0194.     

Optimal buffer allocation in finite closed networks with multiple servers

In this study, we present an optimal buffer allocation procedure for closed queueing networks with finite buffers. The performance measures are evaluated using the expanded mean value analysis, and the solution procedure is incorporated into a nonlinear optimization scheme to arrive at the sub-optimal buffer space vector. The effectiveness of the method is demonstrated through several numerical experiments. Discussions on convergence and computational complexity are also included.     

一类排队服务系统的最优控制策略研究

建立一个双阈值排队服务模型, 用来协调顾客的等待时间和服务系统的运行成本. 采用一种精细的概率分解方法获得瞬态和稳态队长的概率分布性质; 再根据系统稳态性能指标, 建立系统营运利润函数, 并设计一种针对双离散变量函数的全局优化收索算法来研究最优控制策略; 进一步的数值实验揭示出双重阈值策略的优越性.     

Exact analysis of performance models by the Method of Moments

Performance evaluation of distributed systems and service-oriented architectures is often based on stochastic models, such as closed queueing networks which are commonly solved by the Mean Value Analysis (MVA) algorithm. However, the MVA is unable to solve models with hundreds or thousands of users accessing services of multiple classes, a configuration that is often useful to predict the performance of real-world applications. This paper introduces the Method of Moments (MoM), the first exact algorithm for solving closed queueing networks with large population sizes.Compared to the MVA algorithm, which is based on a recursive evaluation of mean queue-lengths, MoM defines a recursion on higher-order moments of queue-lengths that is solved at each step by a linear system of equations. This approach dramatically decreases the costs of an exact analysis compared to the MVA approach. We prove that MoM requires log-quadratic time and log-linear space in the total population size, whereas MVA complexity expressions grow combinatorially as the product of class populations. This extends the feasibility of exact methods to a much larger family of multiclass performance models than those that can be solved by the MVA algorithm.     

A multi-class closed queueing maintenance network model with a parts inventory system

The system we address is a maintenance network of repairable items where a set of bases is supported by a centrally located repair depot and a consumable replacement parts inventory system. If an item fails, a replacement part must be obtained at the parts inventory system before the failed item enters the repair depot. The ordering policy for the parts is the (S,Q) inventory policy. An approximation method for this system is developed to obtain performance measures such as steady-state probabilities of the number of items at each site and the expected backorders at the parts inventory system. The proposed system is modelled as a multi-class closed queueing network with a synchronization station and analyzed using a product-form approximation method. Particularly, the product-form approximation method is adapted so that the computational effort on estimating the parameters of the equivalent multi-class network is minimized. In analyzing a sub-network, a recursive method is used to solve balance equations by exploiting the special structure of the Markov chain. Numerical tests show that the approximation method provides fairly good estimation of the performance measures of interests.     

Modelling Reliability-adaptive Multi-system Operation

This contribution discusses the concept of Reliability-Adaptive Systems (RAS) to multi-system operation. A fleet of independently operating systems and a single maintenance unit are considered. It is the objective in this paper to increase overall performance or workload respectively by avoiding delay due to busy maintenance units. This is achieved by concerted and coordinated derating of individual system performance, which increases reliability. Quantification is carried out by way of a convolution-based approach. The approach is tailored to fleets of ships, aeroplanes, spacecraft, and vehicles (trains, trains, buses, cars, trucks, etc.) - Finally, the effectiveness of derating is validated using different criteria. The RAS concept makes sense if average system output loss due to lowered performance level (yielding longer time to failure) is smaller than average loss due to waiting for maintenance in a non-adaptive case.     

Robust outdoor stereo vision SLAM for heavy machine rotation sensing

The paper presents a robust outdoor stereo vision simultaneous localization and mapping (SLAM) algorithm. It estimates camera pose reliably in outdoor environments with directional sunlight illumination causing shadows and non-uniform scene lighting. The algorithm has been developed to measure a mining rope shovel’s rotation angle about its vertical axis (“swing” axis). A stereo camera is mounted externally to the shovel house (upper revolvable portion of the shovel), with a clear view of the shovel’s lower carbody. As the shovel house swings, the camera revolves with the shovel house in a planar circular orbit, seeing differing views of the carbody top. During the swing, the SLAM algorithm builds a map of observed 3D features on the carbody and simultaneously using these landmarks to estimate the camera position. This estimated camera position is then used to compute the shovel swing angle. Two novel techniques are employed to improve the SLAM algorithm’s robustness in outdoor environments. First, a “Locally Maximal” feature selection technique for Harris corners is used to select features more consistently in non-uniformly illuminated scenes. Another novel technique is the use of 3D “Feature Clusters” as SLAM landmarks rather than individual single features. The Feature Cluster landmarks improve the robustness of the landmark matching and allow significant reduction of the SLAM filter computational cost. This approach of estimating the shovel swing angle has a maximum error of ±1° upon SLAM map convergence. Results demonstrate the improvements of using the novel techniques compared to previous methods.     

Kinematic evaluation of two snow-shovel designs

The objective of this study was to determine how different shovel designs affect trunk motion during snow shoveling. A shovel having a straight shaft and a shovel having a bent shaft were evaluated across three levels of task asymmetry. The primary dependent variables were measures of lumbar kinematics in three directions with respect to the spine (sagittal, rotational, and frontal) recorded with a lumbar motion monitor. Ratings of perceived discomfort and measures of heart rate were also collected. In a laboratory experiment, 12 participants were required to stimulate snow shoveling in three different directions with each shovel. Results showed that the bent shovel significantly reduced the lumbar velocity and acceleration in the sagittal plane without affecting motion in the rotational or frontal planes. Most sagittal and rotational motion parameters increased significantly as throwing direction became more asymmetric. The discomfort ratings indicated that the low back, arms, and wrist were the body regions most severely affected by the task, with some evidence of differences between the two shovel designs.

Relevance to industry

The use of a bent-handled shovel will reduce lumbar sagittal flexion without increasing side bending and twisting during snow-shoveling work. However, the use of multiple shovel designs during snow removal may be needed to reduce discomfort of the upper extremities.     

Performance of laser and radar ranging devices in adverse environmental conditions

A comparative evaluation of millimeter‐wave radar and two‐dimensional scanning lasers in dust and rain conditions for sensor applications in field robotics is presented. A robust and reliable method for measuring the level of suspended dust (or other obscurant media) by determining the transmission coefficient is developed and used for quantitative assessment of sensor performance. The criteria of target acquisition reliability, precision, and accuracy under varying environmental conditions are assessed via sensor operation in a controlled environment. This environment generated dust and rain of varying densities. Sensor performance is also assessed for the potential effect on digital terrain mapping and haul truck localization due to sensor‐specific behaviors in these conditions (e.g., false targets, increased noise). Trials on a research electric face shovel are conducted to test observed behaviors. It is concluded that laser scanners are suitable for environments with transmissions exceeding 92%–93%/m for targets closer than 25 m. The radar remained relatively unaffected by the generated conditions of rain (50–70 mm/h) and dust (10‐m visibility); however, its accuracy (0.1 m with a corner reflector and 0.3 m on a haul truck), free‐space clutter, and scan rate were insufficient for locating unmodified haul trucks for this application. © 2009 Wiley Periodicals, Inc.     

The perceived effect of breakdown and repair on the performance of multiprocessor systems

It is argued that classical measures of computer system performance, for example mean response time, are inadequate in the context of fault-tolerant system design. Alternative, perception-based measures are proposed and theorems established describing their properties. Focus is directed upon the homogeneous M/M/m system in which total processor power is constrained by budget and processors are subject to failure and repair. A numerical technique for extracting both classical and perception-based measures from the associated two-dimensional Markov process is offered, along with bounds on time and space required for its execution. It is seen that the perception-based approach to system design can call for twice as many processors as the classical approach.     

GI/Gm排队系统梯度估计的一种新方法

梯度估计是研究复杂离散事件动态系统的关键问题之一.这里对GI/G/m排队系统提 出一种新方法,在一次采样(仿真)的基础上,通过分析采样路径,可得到性能指标关于参数的 局部函数表达式.由此可直接求导,得到采样梯度,并证明了由该方法得到的梯度估计的无偏 性.该方法计算量小、精度高,还可以进一步拓广到其它系统上.     

随机任务在云计算平台中能耗的优化管理方法

针对云计算系统在运行过程中由于计算节点空闲而产生大量空闲能耗,以及由于不匹配任务调度而产生大量“奢侈”能耗的能耗浪费问题,提出一种通过任务调度方式的能耗优化管理方法.首先,用排队模型对云计算系统进行建模,分析云计算系统的平均响应时间和平均功率,建立云计算系统的能耗模型.然后提出基于大服务强度和小执行能耗的任务调度策略,分别针对空闲能耗和“奢侈”能耗进行优化控制.基于该调度策略,设计满足性能约束的最小期望执行能耗调度算法ME3PC(minimum expectation execution energy with performance constraints).实验结果表明,该算法在保证执行性能的前提下,可大幅度降低云计算系统的能耗开销.     

The optimum lift angle for the culinary spatula (turning shovel)

A culinary spatula (turning shovel) is one of the common cooking tools used in the Oriental kitchen. Since the use of a turning shovel may cause cumulative trauma to the wrist, the spatula angle for food frying, food turning, and food shovelling was investigated. The subjects were eight female students who were experienced cooks. Handle angle significantly affected both performance and subjective rating. The optimum angle is 25°.     

Applications of queueing structures in manufacturing systems

This survey paper discusses and, to some extent, identifies manufacturing sub-systems that can be represented using accepted queueing models. Aggregate performance measures can be obtained through application of these models. Depending on the complexity of the congestion characteristics of the system, the standard results from queueing theory texts may yield guidelines for selection of optimal operational parameters.     

Methodology for predicting performance of distributed and parallel systems

This paper describes an accurate and efficient method to model and predict the performance of distributed/parallel systems. Various performance measures, such as the expected user response time, the system throughput and the average server utilization, can be easily estimated using this method. The methodology is based on known product form queueing network methods, with some additional approximations. The method is illustrated by evaluating performance of a multi-client multi-server distributed system. A system model is constructed and mapped to a probabilistic queueing network model which is used to predict its behavior. The effects of user think time and various design parameters on the performance of the system are investigated by both the analytical method and computer simulation. The accuracy of the former is verified. The methodology is applied to identify the bottleneck server and to establish proper balance between clients and servers in distributed/parallel systems.