Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. A GENERIC SIMULATION MODEL FOR SELECTING FLEET SIZE IN SNOW PLOWING OPERATIONS Yipeng Li Zhen Lei Shuoyan Xu Lingzi Wu Simaan AbouRizk Tae J. Kwon Department of Civil and Environmental Engineering Department of Civil Engineering University of Alberta University of New Brunswick Edmonton, AB T6G 2W2, CANADA Fredericton, NB E3B 5A3, CANADA ABSTRACT Accumulated snow on roads poses a threat to traffic systems and rouses significant safety concerns. Snow plowing is often used to recover roads in the event of heavy snow. Due to the unpredictability of weather conditions, it is difficult to determine the overall performance of a certain truck fleet size, thus make it challenging to estimate the number of snow plow trucks needed for a given highway area. The objective of this research is to estimate the truck fleet performance under uncertain weather conditions, and to provide decision support for selecting a reasonable fleet size. A generic simulation model is developed in the Simphony.NET environment. Weather, road network, and truck speed data are entered as inputs, and Monte Carlo simulation is used to generate random snow events to quantify the performance. A case study is developed and presented to demonstrate the practicality and feasibility of the proposed model. 1 INTRODUCTION Winter road maintenance is challenging for many northern countries (Shi 2010). Notably, Canada spends around $1 billion dollars annually in winter road maintenance activities (Andrey et al. 2001). In practice, snow plowing plays a significant role in winter road maintenance to remove as much loose snow on the roads as possible, and to increase mobility and safety (Perrier et al. 2006; Usman et al. 2010). In order to conduct snow plowing activities effectively, efforts have been made to improve planning efficiency. One major aspect of optimizing snow plowing activities is the selection of the truck fleet size and the plowing routes. In previous studies, snow plow routing optimization is considered as a Hierarchical Chinese Postman Problem (HCPP) (Cabral et al. 2004; Ghiani and Improta 2000). The common solution for this problem is to divide the area into several sectors and set one depot at each sector with an assigned truck crew. When the snowstorm comes, trucks will depart from the depot to different road sections and return to the same depot after all roads are cleaned. Due to the complexity of snow plowing operations, however, the challenge is separating a large road network into small sectors and determining the crew size at each depot (Stricker 1970). For example, the size of each sector will affect its crew size. Both the crew size and the combination of roads within this sector must be considered when selecting the plowing route. Additionally, uncertain weather conditions can stall this process because the snow coverage areas by storms are unknown. As such, the roads need to be plowed, and the plowing route varies for each snow event. Considering the random nature of weather events is necessary to resolve these problems. The process of developing simulation models often requires repetitive efforts; a generic model is needed to incorporate the planning process of snow plowing on various road networks. This paper therefore proposes a generic model to simulate snow plowing processes under uncertain weather conditions. This 2966 978-1-7281-3283-9/19/$31.00 ©2019 IEEE