Budget Allocation for Steel Bridge Paint Maintenance

Abstract

Government authorities are responsible for managing their available budget so that they gain maximum benefit. Therefore, they must make intelligent decisions as to which projects will be funded and the degree of funding. Dynamic programming (DP), integer programming (IP), and greedy heuristic (GH) approaches have been applied to optimize a two-year budget allocation for repainting steel bridges in Indiana. The optimal solution and the objective function values resulting from application of DP, IP, and GH are similar. The Indiana Department of Transportation (INDOT) divides Indiana into six districts. The results show that District 1 has the highest budget allocation percentage (28%). It has the lowest percent in the first year and the highest percent in the second year. District 2 has the lowest percentage (11%). A sensitivity analysis has been completed to show the potential alternative solutions that assist INDOT decision makers in solving their budget allocation problems.