چكيده به لاتين
In this thesis, the pavement Maintenance and Rehabilitation (M&R) planning has been considered in several respects; initially, by producing a parametric deterministic model of multi-year pavement M&R planning, it was possible to determine the type of pavement M&R treatments at the network level. Then, the stochastic characteristics of the future budget were considered in the development of the model. To this end, the model has been developed in the form of a two-stage stochastic model that, while considering the possible effects of future budgets on results, if the projected budget is not realized and deducted, the plan does not need to be revised. In the end, a two-stage stochastic model was developed as a robust optimization model. In this way, the possibility of additional financing through interest-bearing loans is also provided in the planning process. In the robust optimization method, the model was developed in such a way that, if additional funding is required, the program does not need to be re-evaluated.
Choosing the appropriate objective function is also one of the topics discussed in this thesis, which has been considered in the production of the deterministic model. To this end, three different objective functions have been defined and based on the results of the model solving for a case study, the appropriate target function has been selected. All three objective functions are defined in terms of cost and as a minimization function and, in brief, follow three approaches; In the first objective function, the organizational budgeting approach has been considered, meaning that the goal was to reduce the cost difference between the admintration cost (the cost of performing M&R operations) and the budget, and at the same time, the improvement of the network condition has been followed every year since the analysis period. The second objective function was meta-organizational approach and sought to reduce the total network costs, including the admintration cost (the cost of M&R operations), the operation vehicle cost and the user's delay cost resulting from the M&R operation. In the third objective function, the meta-organization approach was canverted to a comprehensive approach which, in addition to reducing all the cost of the meta-organization approach, has also followed the improvement of the network condition at the end of the analysis period.
In the following, using the data from a case study, the most appropriate objective function was first selected based on the lowest cost, which was the same as the third objective function. It has then been proved that considering the details on the network level, it can help increase the speed of the model solving in the GAMS software, and, in addition to determining the M&R policy, will also determine the type of M&R treatment. Increasing the speed of the model solving is important in establishing a pavement M&R plan for networks with a large number of segments, as well as for mid-term and long-term analysis periods. Then it was determined that the probable conditions of budgeting can be considered at the beginning of the planning, so that there is no need to review the plan during the analysis period.
In summary, the results of producing and solving deterministic, two-stage stochastic and robust models for case study data are as follows:
• With the production of the parametric deterministic model of M&R planning, it is possible to allocate pavement M&R treatments in addition to determining the M&R policy.
•By developing the two-stage stochastic model of pavement M&R planning under uncertain budget, it has been proven that in the case of a budget deficit, the pavement M&R plan does not need to be revised during the analysis period.
•By developing the robust model of pavement M&R planning, it is possible to achieve a sustainable plan, regardless of whether it is subject to a deficit budgeting or additional financing.
