Efficient Simulation of Population Overflow in Parallel Queues

In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal” state-dependent change of measure without the need for difficult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traffic intensities yield asymptotically efficient estimates (with relative error increasing sub-linearly in the overflow level) where no other state-independent importance sampling techniques are known to be efficient. The efficiency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.\u

Efficient Heuristics for the Simulation of Buffer Overflow in Series and Parallel Queueing Networks

Many of recent studies have proved the tail equivalence result for Egalitarian Processor Sharing system: [EQUATION], where B (resp. V) is service requirement (resp. sojourn time) of a customer; for PS, g = 1 - ρ. In this paper, we consider time-shared systems in which the server capacity is shared by existing customers in proportion to (dynamic) weights assigned to customers. We consider two systems, 1) in which the weight of a customer depends on it Age (attained service), and 2) in which the weight depends on the residual processing time (RPT). We allow for a parameterized family of weight functions such that the weight associated with a customer that has received a service (or, has a RPT) of x units is ω(x) = xα for some -∞ < α < ∞. We then study the sojourn time of a customer under such scheduling discipline and provide conditions on α for tail equivalence to hold true, and also give the value of g as a function of α

Analysis of State-Independent Importance-Sampling Measures for the Two-Node Tandem Queue

We investigate the simulation of overflow of the total population of a Markovian two-node tandem queue model during a busy cycle, using importance sampling with a state-independent change of measure. We show that the only such change of measure that may possibly result in asymptotically efficient simulation for large overflow levels is exchanging the arrival rate with the smallest service rate. For this change of measure, we classify the model's parameter space into regions of asymptotic efficiency, exponential growth of the relative error, and infinite variance, using both analytical and numerical techniques

Job-shop scheduling with approximate methods

Imperial Users onl

AN INTEGRATED TRAFFIC CONTROL SYSTEM FOR FREEWAY CORRIDORS UNDER NON-RECURRENT CONGESTION

This research has focused on developing an advanced dynamic corridor traffic control system that can assist responsible traffic professionals in generating effective control strategies for contending with non-recurrent congestion that often concurrently plagues both the freeway and arterial systems. The developed system features its hierarchical operating structure that consists of an integrated-level control and a local-level module for bottleneck management. The primary function of the integrated-level control is to maximize the capacity utilization of the entire corridor under incident conditions with concurrently implemented strategies over dynamically computed windows, including diversion control at critical off-ramps, on-ramp metering, and optimal arterial signal timings. The system development process starts with design of a set of innovative network formulations that can accurately and efficiently capture the operational characteristics of traffic flows in the entire corridor optimization process. Grounded on the proposed formulations for network flows, the second part of the system development process is to construct two integrated control models, where the base model is designed for a single-segment detour operation and the extended model is designated for general network applications. To efficiently explore the control effectiveness under different policy priorities between the target freeway and available detour routes, this study has further proposed a multi-objective control process for best managing the complex traffic conditions during incident operations. Due to the nonlinear nature of the proposed formulations and the concerns of computing efficiency, this study has also developed a GA-based heuristic along with a successive optimization process that can yield sufficiently reliable solutions for operating the proposed system in a real-time traffic environment. To evaluate the effectiveness and efficiency of the developed system, this study has conducted extensive numerical experiments with real-world cases. The experimental results have demonstrated that with the information generated from the proposed models, the responsible agency can effectively implement control strategies in a timely manner at all control points to substantially improve the efficiency of the corridor control operations. In view of potential spillback blockage due to detour operations, this study has further developed a local-level bottleneck management module with enhanced arterial flow formulations that can fully capture the complex interrelations between the overflow in each lane group and its impact on the neighboring lanes. As a supplemental component for corridor control, this module has been integrated with the optimization model to fine-tune the arterial signal timings and to prevent the queue spillback or blockages at off-ramps and intersections. The results of extensive numerical experiments have shown that the supplemental module is quite effective in producing local control strategies that can prevent the formation of intersection bottlenecks in the local arterial

Message-driven dynamics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 251-260).by Richard Anton Lethin.Ph.D