Abstract
Ensuring a transportation system’s operational efficiency and effectiveness is a challenge particularly for road maintenance agencies in winter times. Winter road maintenance involves snow plowing and chemicals/abrasives spreading, and both are performed by using a number of specific types of trucks. However, most departments of transportation do not maintain sufficient trucks and hence they may resort to contract additional equipment to make up for the shortfall. Based on the Newsvendor problem, this study develops a novel stochastic model to optimize the number of plows that should be contracted prior to a snow season to minimize the total cost, considering the frequency and distribution of various intensities of snow events, geometric condition of the roadways and traffic speeds. A solution methodology based on stochastic modeling is proposed and applied to a numerical example utilizing actual snow data. Additionally, a sensitivity analysis is performed to evaluate the impact of model parameters on the optimum solution.
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