Optimization techniques for planning highway pavement (surface) improvements

In this paper, two different decision models for the planning of highway pavement improvements are presented. In the first model, the authors want to get a prescribed improvement in the state of the highway network with minimal agency cost. In the second model, a given amount of money is distributed between the highway sections in different states in such a way that the achieved improvements should be the best in some sense. The first model helps the administration in the estimation of the necessary cost for the annual highway improvements. The second model in addition gives an object tool to the administration for the distribution of the total amount of money between the different regions of the country. The authors present the construction of the models in detail. Both of them use Markov transition probabilities according to the states of the highway sections and produce a special structure, large-scale, linear programming problem. Some numerical results are presented on the data from Hungarian highways.