An optimisation tool to select gravel roads for dust chemical treatment projects using genetic algorithms

ABSTRACT

As part of the Wyoming Technology Transfer Center (WYT2/LTAP) efforts to develop a Gravel Roads Management System (GRMS) in Wyoming, this research study developed a user-friendly tool, using JavaScript, that implements an optimisation model based on genetic algorithms (GA). The developed tool will help decision-makers and local agencies in allocating the limited Congestion mitigation and air quality (CMAQ) programme funds efficiently among the different gravel roads. To select gravel roads for chemical treatment projects, the implemented GA searches for an optimum set of roads in a way to maximise the overall dust reduction and the environmental benefits gained from suppressing dust. The established optimisation model considers different factors related to the road itself such as the amount of fines in the surfacing materials, Average daily traffic (ADT), average driving speed, and moisture content. In addition, it considers different factors related to the surrounding environment such as oil production rates, annual rainfall, average monthly temperatures, agricultural lands and households. The developed tool can be applied on large scale gravel road networks, enhance the funding allocation process, increase the reflected welfare on the local economy, and imply a sort of general satisfaction among the different competing parties for CMAQ funds.

KEYWORDS:

• Optimisation
• gravel roads
• dust
• genetic algorithms
• pavement management system (PMS)
• dust suppressants

Acknowledgements

The authors would like to thank Mountain Plains Consortium (MPC), Wyoming Counties, and (WYDOT) for supporting this research study.

Disclosure statement

No potential conflict of interest was reported by the authors.