Developing a Gis-Based Fleet Optimization Model for Winter Maintenance Operations

Abstract

AbstractIn the annual winter route maintenance, the Kansas Department of Transportation (KDOT) in the United States spends substantial resources and multiple fleets of snow-plow trucks on snow and ice control activities and operations. The deployment of a large fleet size over a vast maintenance area creates an operational problem in determining the optimal maintenance routes and fleet size. This study aimed at supporting winter maintenance operations of KDOT by developing a snow-plow fleet optimization model to enhance the efficiency of snow and ice route removal by justifying the feet size and determining where to allocate limited resources during snow events. The fleet optimization model was developed using geographic information system (GIS) base-maps created by a commercial software package, ArcGIS, and its extensions. As a result, the developed optimization model minimized the fleet size and maintain the current level of service for all snow and ice routes. The model was tested with a District in KDOT. The results show that four snow-plow trucks could be removed from the current fleet while the level of service is maintained at 79.72%. In addition, the optimization model also decreased the total travel time needed to treat all snow and ice routes in the selected District by approximately 24.3 h for one treating iteration. The result of this study is expected to apply to other Districts in Kansas after successfully conducting a pilot study in the selected District.