2015
EMSS 2015 Proceeding
Stochastic programming for train distribution in a metro transportation system
Authors: Jorge A. Garcia, Kumaraswamy Ponnambalam
Abstract
We present a mixed integer linear programming formulation with an application for the optimal train distribution problem. The objective was to assign trains to metro routes so that the sum of deficit capacity costs (i.e., passengers that cannot be carried) and the overcapacity costs (i.e., the number of empty seats) in a metro transportation system were minimized. We selected Mexico City?s Metro Transportation System (MTS) as a study case. We narrowed our model to the operation and demand of peak hours. First, we solve a deterministic model using mean values for the parameters. Then, we built a two-stage stochastic model to include uncertainty into the parameters and we calculated estimates for mean and variance using maximum likelihood estimation. We discuss the results and compare the solutions for the four cases that we created. Finally, we propose an extension of the model that includes a time index.
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