Post-Pareto optimality approach to enhance budget allocation process for bridge rehabilitation management

A variety of conflicting criteria in the form of objective functions exist in budget allocation optimisation problem for bridge rehabilitation projects. Budget allocation decision-making for such transportation assets is generally a combinatorial problem. The nature of the problem is a good reason for decision-makers to apply multi-objective optimisation techniques. However, manually choosing an acceptable solution from a set of optimal solutions is a time-consuming task, which would be avoided if the optimisation technique could be followed by a ranking method to obtain unique acceptable solution. To enhance the budget allocation process, this paper develops a posteriori approach to prioritise Pareto-Optimal (PO) solutions generated by genetic algorithm in order to identify a unique package of bridge rehabilitation activities. By identifying the most conventional objective functions for bridge rehabilitation based on technical and managerial criteria, a multi-objective knapsack problem is constructed. PO solutions will then be prioritised applying ‘Technique for Order Preference by Similarity to an Ideal Solution’. The feasibility of the study will be finally demonstrated through an illustrative example. The proposed ranking approach may facilitate the budget allocation optimisation process for bridge rehabilitation where one or a few acceptable solutions are demanded.