Developing an Optimization Tool for Selecting Gravel Roads Maintenance Strategies using a Genetic Algorithm

Abstract

As part of the efforts by Wyoming Technology Transfer Center (WYT2/LTAP) to develop a gravel roads management system (GRMS) in Wyoming, this research study developed a user-friendly tool, using JavaScript, which implements an optimization model based on genetic algorithms (GA). The developed tool will help decision makers and local agencies in managing gravel roads efficiently. Using this tool, a decision maker will be able to identify the most appropriate treatment type for each road, based on service level, estimated project costs, predicted road conditions, and whether to fund a project or not. The optimization model aims to maximize the overall condition of the gravel roads network subject to the average daily traffic (ADT) on each road. The developed tool can be applied to large-scale optimization problems (i.e., gravel roads network). The tool operates with minimal data requirements that are in line with procedures regularly followed at these agencies. In addition to having an engineered outcome, this tool can help local agencies in allocating their limited available funds efficiently, enhancing the planning process, maximizing the social welfare of the local economy, and promoting a sense of general satisfaction within the local community. A case study using data from Laramie County was used to validate this tool. The initial results were promising and in line with previous efforts to manage gravel roads in Wyoming.