Abstract
This paper considers a hazardous materials (hazmat) transportation network design problem based on hub location topology under uncertainty. The control variables include decisions regarding location of hubs and hazmat response teams, along with the routing schemes. The model aims to minimize the total risk in the network. The measure of risk incorporates average response time to hazmat incidents as well as waiting time at hubs. To tackle the uncertainty of the problem, an efficient interactive approach using mean-absolute deviation and possibilistic programming is developed. Two heuristic algorithms based on lower bound procedure and rolling horizon scheme are presented to solve the model in large scale instances. The advantages of the presented methodologies are demonstrated through numerical experiments based on transportation networks from Sioux Falls, SD, and Western New York. We investigate different design schemes and discuss optimal decisions under different configurations.
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