Optimizing the Inspection Schedule for Bridge Networks

Abstract

Optimizing the inspection route for a bridge network is a paramount factor in reducing inspection duration and cost, particularly for bridges located in a large geographical area. Accordingly, this study presents a Bridge Network Inspection Planning (BNIP) model, which aims to minimize the total inspection cost by reducing traveling distance, accommodation cost, wasted time, and inspection team cost. In this model, a Discrete Event Simulation model was built to estimate the inspection duration for each bridge in the network, whereas Genetic Algorithm (GA) approach was used to optimize the inspection route. Web scraping technique was utilized to develop a geospatial information algorithm dedicated to extracting the actual driving distance between any two points in the inspection route. The model was tested against a real bridge network in the Illinois State, USA. The model provides strong guidance for consultants and authorities in charge of bridges in planning the upcoming inspection activities.