Mathematical model for optimizing snow removal
Kaj Holmberg, a professor at Linköping University, felt that snow removal could be made more efficient and received support from the Swedish Research Council, as well as researcher Roghayeh Hajizadeh from Iran. Together, they focused on the recurring problems posed by the winter season and mathematically modelled them to develop solutions.-I come from the coldest part of Iran, where it also snows. I moved here and realized there was room for improvement in snow removal, says Roghayeh.
Identified challenges for making snow removal more efficient have included determining the order in which streets should be cleared, which vehicle should clear which street, and which route they should choose. Other challenges have included the need to clear different types of roads with different types of vehicles, such as cycle paths and pedestrian areas. Through optimization, researchers have been able to present solutions to streamline snow removal.
Efficiency to achieve global goals
The conclusion has been presented in the thesis "Optimization of Snow Removal in Cities" written by Roghayeh. The thesis explains how to calculate optimal routes for snow removal vehicles to minimize the time taken for snow clearance. Efficient snow removal would not only save time but also reduce environmental impact and decrease costs for society. It would be a significant contribution to achieving global goals such as "Sustainable Cities and Communities" and "Climate Action”. By streamlining snow removal, one can contribute to a sustainable, inclusive urban environment and reduce emissions to promote environmental and economic well-being worldwide. Improved accessibility would also lead to more efficient freight and passenger transportation, reducing the risk of accidents and consequently lowering healthcare costs.Municipal task to implement new approaches
The researchers see the biggest challenge ahead not in snow removal itself but in implementing the new approach. They have developed a tool that solves many societal problems but still faces some challenges.-It's the contractors driving around and clearing snow who should use the solution, and their clients are often municipalities, who should instruct them to use this tool. And we're not there yet, says Kaj.
Nevertheless, the researchers are hopeful for the future. The theoretically most challenging task, academic research, has been completed. Now, only the application remains.
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