Optimization module for bridge maintenance and improvements in the state of Alabama.

摘要

In Alabama, the bridge population is aging, and many bridges have safety or capacity problems, and funding is limited. What is needed is a bridge management system (BMS) that systematically evaluates bridges for maintenance, rehabilitation, and replacement and allocates available funds in the most cost-effective manner. The Alabama Highway Department (AHD) contracted The University of Alabama to develop a BMS. From that activity an Alabama Bridge Information Management System (ABIMS) was designed. As part of ABIMS, an "optimization module" was needed as a tool for bridge managers to identify critical bridges and allocate available funds.;The goal of this research was to investigate optimization models, select one, and, using available information, modify it to fit Alabama's needs. The AHD had already investigated and, narrowed the field to two practical choices, PONTIS and OPBRIDGE. This research further investigated these two possibilities. ABIMS committee decided to adopt North Carolina's OPBRIDGE as the model to use for Alabama.;All required data and parameters to run OPBRIDGE were identified and evaluated. A comparison of Alabama's available data was made to determine if any required information was not available in Alabama records. Each piece of missing data was analyzed and recommendations were made to accommodate OPBRIDGE. All other required parameters and data were validated or modified. The source code was modified to accommodate any required changes. OPBRIDGE was renamed ALBRIDGE since all the parameter tables were converted to Alabama data, and there was an extensive amount of code change. After ALBRIDGE was operating with Alabama parameters and bridge data, any observed problems were identified and corrected.;The program was tested, and test results were reviewed by the AHD personnel. ALBRIDGE performed satisfactorily. Alabama bridge managers now have a working tool to better manage limited funds and improve bridge conditions in the state.;There are several parameters being used in the model that have a limited amount of validating data. It is recommended that AHD study the parameters in more detail to fine tune the model and make it a better tool.