Virtual Learning

MPC Research: Optimizing Snowplowing Operations

• May 26, 2022
  Virtual Learning (desktop/laptop and mobile devices)

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Description

Optimizing Snowplowing Operations in Utah via routing and truck allocation considers a two-stage planning problem where a fleet of snow plow trucks is first divided among a set of independent regions and then each region designs routes for efficient snow removal. In the first stage, we run routing heuristic to optimize the plowing routes with the goal of minimizing the total travel time. Compared with the original routes operated by UDOT, the proposed routes reduce the total travel time by 5.04% on average across all regions. In the second stage, we design a custom branch-and-bound algorithm to allocate trucks such that the maximum turnaround time across all the regions is minimized. The resulting allocation reduces the turnaround time by more than 20% compared to the original allocation.

Speaker(s)

Yinhu Wang is currently working towards a Ph.D. at the Department of Civil & Environmental Engineering, U of U. He received a master degree in Transportation Engineering from Beijing Jiatong University, China in 2018. His research interests include traffic modeling, vehicle routing optimization and data-driven facility location optimization.

Target Audience

Maintenance staff to include operators, mechanics, material suppliers, decision makers, equipment specification writers and anyone else that has an interest or impact on snow and ice control operations.