# Decision Support Model for Allocating Maintenance Budgets for Bridges
## 2 Literature Review
### Previous Studies  
[PERSON] et al. [16] applied the MAUT for bridge maintenance planning in the Netherlands road network, through the case study. The considered performance indices are bridge condition index, cost to the owner, users' experienced delay cost, and environmental cost. The study has established a single utility function for each of these indicators. Each of these indicators has a given weight out of 100. For each bridge these attributes are given a score, then the score is multiplied by the weight of the same indicator. [PERSON] et al. [17] utilized the AHP concept to compare between the criteria to evaluate the historical pedestrian bridges in Croatia. Following that, evidential reasoning was used to assess bridges against each criterion. After that, bridges were ordered using the TOPSIS technique. The criteria identified by them are bridge condition, the complexity of bridge rehabilitation, bridge load, last rehabilitation, rehabilitation cost, cost of waste material disposal, required time for rehabilitation, required time for document preparation, preservation of cultural heritage, tourist attraction, and historical importance. [PERSON] and [PERSON] [18] utilized the AHP to determine the weight of the structural components and subcomponents of bridges. The study utilized a five-point scale to assess the condition of each structural component of the bridge under consideration. The study then determined the overall bridge health index using the AHP weights and condition states for each component of the bridge. As the bridge health index approaches 100, it means that the bridge is in good health and requires no maintenance. [PERSON] and [PERSON] [19] developed a prioritization model for the maintenance operations of road facilities. The MAUT was also used to assist in the decision-making process for the maintenance of road facilities. The prioritization attributes for bridges were identified along with other road elements such as roadside elements and traffic control devices. The prioritization attributes were then weighted with the help of local experts in Thailand. The bridge with a higher utility value is more prioritized. They identified six objectives and a total of fourteen performance indicators. [PERSON] et al. [20] developed a knowledge-based system for bridge maintenance. The system has three functions--setting maintenance priority, evaluation of feasible treatment, and maintenance planning. The priority is determined by ranking several parameters, including type of defect, traffic load, environmental conditions, age of the bridge, types of foundation, and superstructure. Each of these factors has sub-factors and corresponding weights. From these weights the priority index is determined using model score equation. Following that, each possible treatment is evaluated by lifetime to cost ratio. Finally, the maintenance plan is evaluated by the cost and effectiveness of the selected treatment and the number of cases treated using model equations developed by the authors. [PERSON] et al. [21] developed a systematic methodology for condition assessment for historical road bridges based on the knowledge approach using fuzzy logic and sets of a-cuts. They divided each bridge into three components--substructure, superstructure, and equipment. These components were further divided into elements. After that, these elements were evaluated by experts and, using the fuzzy theory, each component condition rating was defined. AHP was used for the comparisons of components to find the relative importance of each component. The overall bridge condition rating is found by summing the multiplication of the components ratings by their relative importance defined from the AHP. The resulted value is called Historic Road Bridge Condition Assessment Index (HRBCAI). [PERSON] and [PERSON] [22] proposed a decision model that assists in determining maintenance prioritization for a set of bridges with constrained budget.