Application of semi-analytical finite element method to analyze asphalt pavement response under heavy traffic loads

Accurate assessment of the impact of heavy traffic loads on asphalt pavements requires a computational model which is able to calculate the response of the pavement fast and precisely. Currently the most finite element analysis programs based on traditional methods have various limitations. A specific program SAFEM was developed based on a semi-analytical finite element method to overcome the problems. It is a three-dimensional FE program that requires only a two-dimensional mesh by incorporating the semi- analytical method using Fourier series in the third dimension. The computational accuracy and efficiency of the program was verified by analytical verification previously. The experimental verification is carried out in this paper and the results show that the SAFEM is able to predict the mechanical responses of the asphalt pavement. Using the program SAFEM, the impact of heavy traffic loads was analyzed in terms of stress and strain dis- tribution, surface deflection and fatigue life. The results indicate that if the asphalt pave- ment is subjected to the heavy traffic load more, the thicknesses and stiffness of the pavement structural layers should be increased adequately in order to support the surface deflection, The compressive stress in asphalt binder course is relatively large and increases more significantly compared with that in the other asphalt layers when the axle load becomes larger. With comparison of the predicted fatigue life, the increase of the axle load will lead to the destruction of the asphalt pavement extremely easily.

Diffusion approximations for multiclass queueing networks under preemptive priority service discipline

We prove a heavy traffic limit theorem to justify diffusion approximations for multiclass queueing networks under preemptive priority service discipline and provide effective stochastic dynamical models for the systems. Such queueing networks appear typically in high-speed integrated services packet networks about telecommunication system. In the network, there is a number of packet traffic types. Each type needs a number of job classes （stages） of processing and each type of jobs is assigned the same priority rank at every station where it possibly receives service. Moreover, there is no inter-routing among different traffic types throughout the entire network.

MANY-SERVER QUEUES WITH CUSTOMER ABANDONMENT:A SURVEY OF DIFFUSION AND FLUID APPROXIMATIONS

The performance of a call center is sensitive to customer abandonment. In this survey paper, we focus on G/GI/n ＋ GI parallel-server queues that serve as a building block to model call center operations. Such a queue has a general arrival process （the G ）, independent and identically distributed （iid） service times with a general distribution （the first G1 ）, and iid patience times with a general distribution （the ＋GI）. Following the square-root safety staffing rule, this queue can be operated in the quality- and efficiency-driven （QED） regime, which is characterized by large customer volume, the waiting times being a fraction of the service times, only a small fraction of customers abandoning the system, and high server utilization. Operational efficiency is the central target in a system whose staffing costs dominate other expenses. If a moderate fraction of customer abandonment is allowed, such a system should be operated in an overloaded regime known as the efficiency-driven （ED） regime. We survey recent results on the many-server queues that are operated in the QED and ED regimes. These results include the performance insensitivity to patience time distributions and diffusion and fluid approximate models as practical tools for performance analysis.

OPTIMAL CONTROL OF AN M/G/1 RETRIAL QUEUE WITH VACATIONS

In this note, we consider an M/G/1 retrial queue with server vacations, when retrial times, service times and vacation times are arbitrary distributed. The distribution of the number of customers in the system in stationary regime is obtained in terms of generating function. Next, we give heavy traffic approximation of such distribution. We show that the system size can be decomposed into two random variables, one of which corresponds to the system size of the ordinary M/G/1 FIFO queue without vacation. Such a stochastic decomposition property is useful for the computation of performance measures of interest. Finally, we solve simple problems of optimal control of vacation and retrial policies.

Diffusion Approximation of a Multitype Re-entrant Line under Smaller-buffer-first-served Policy

This paper studies a multitype re-entrant line under smaller-buffer-first-served policy, which is an extension of first-buffer-first-served re-entrant line. We prove a heavy traffic limit theorem. The key to the proof is to prove the uniform convergence of the corresponding critical fluid model.

Hierarchical modeling of stochastic manufacturing and service systems

This paper presents a review of methodologies for analyzing stochastic manufacturing and service systems. On the basis of the scale and level of details of operations, we can study stochastic systems using micro-,meso-, and macro-scopic models. Such a classification unifies stochastic modeling theory. For each model type,we highlight the advantages and disadvantages and the applicable situations. Micro-scopic models are based on quasi-birth-and-death process because of the phase-type distributed service times and/or Markov arrival processes.Such models are appropriate for modeling the detailed operations of a manufacturing system with relatively small number of servers(production facilities). By contrast,meso-scopic and macro-scopic models are based on the functional central limit theorem(FCLT) and functional strong law of large numbers(FSLLN), respectively, under heavy-traffic regimes. These high-level models are appropriate for modeling large-scale service systems with many servers, such as call centers or large service networks. This review will help practitioners select the appropriate level of modeling to enhance their understanding of the dynamic behavior of manufacturing or service systems. Enhanced understanding will ensure that optimal policies can be designed to improve system performance. Researchers in operation analytics and optimization of manufacturing and logistics also benefit from such a review.