Extended Hypercube Models for Large Scale Spatial Queueing Systems

Boyacı, Burak and Geroliminis, Nikolas (2012) Extended Hypercube Models for Large Scale Spatial Queueing Systems. In: 91st Annual Meeting of the Transportation Research Board, 2012-01-22 - 2012-01-26.

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Abstract

Different than the conventional queueing systems, in spatial queues, servers travel to the customers and provide service on the scene. This property makes them applicable to emergency response (e.g. ambulances, police, fire brigades) and on-demand transportation systems (e.g. shuttle bus services, paratransit, taxis). The difference between the spatial queues and conventional queueing systems is various types of customers and servers and different service rates for different customer-server pairs. For the Markovian arrival and service characteristics, one of the methods to find system performance measures is to model and calculate steady state probability of the Markov chain for the hypercube queueing model. One of the obstacles on the way to apply hypercube queueing models to real life problems is the size of the problem; it grows exponentially with the number of servers and a linear system with exponential number of variables should be solved for each instance. In this research, in order to increase scalability of the problem, we propose two new models. In addition to that, we modeled the problem by using Monte Carlo simulation and tested the convergence and stability properties of the simulation results and compare them with stationary distributions. In the final part, a mixed integer linear programming formulation is given for optimal server configuration with different objectives improving different performance measures. As a future work, we are planning to use the optimal solutions of this formulation to evaluate different dispatching policies.

Item Type:
Contribution to Conference (Paper)
Journal or Publication Title:
91st Annual Meeting of the Transportation Research Board
ID Code:
135563
Deposited By:
Deposited On:
22 Jul 2019 09:55
Refereed?:
Yes
Published?:
Published
Last Modified:
27 Feb 2024 01:57