Transportation Programming (TP) plays an important role in the development of the infrastructure of a country. Given the limited budget, it is a challenging decision to select the projects to be funded and implemented from the numerous options. The problem is complicated by the fact that some of the potential projects are interdependent. The benefit (and/or the cost) of the joint project combining multiple projects can be different from the sum of the benefits (and/or the costs) if the associated projects are implemented separately. Besides, some projects cannot be selected at the same time as they are incompatible or exclusive to each other by nature. The typical examples are the projects utilizing the same resource, such as a piece of land. In addition, much more attention nowadays is paid to the fairness of budget allocation and the balance of regional development as the society becomes more democratic and diversified. Thus, in order to address the equity issue and the political feasibility, a new integer programming (IP) model based on the set covering problem (SCP) has been proposed to ensure that the regional balance issue is addressed. This SCP-based model, with the constraints taking into account the budget limitation and the projects' mutual exclusivity, is transformed into a linear programming (LP) model by Lagrangian Relaxation (LR). The key theme of this study is then to design the solution algorithm that can efficiently adjust the LP multipliers and find the feasible solutions so as to achieve a high-quality approximate solution within an acceptable computation time. Finally, a numerical experiment that can reflect the practical situations is performed to validate the applicability of the developed model and solution algorithm.
|Number of pages||11|
|Journal||Transportation Research Part C: Emerging Technologies|
|State||Published - 1 Jan 2013|
- Lagrangian Relaxation
- Set covering problem
- Transportation programming