Risk-based Multiobjective Optimization Model for Bridge Maintenance Planning

Abstract

Determining the optimal maintenance plan is essential for successful bridge management. The optimization objectives are defined in the forms of minimizing life‐cycle cost and maximizing performance indicators. Previous bridge maintenance models assumed the process of bridge deterioration and the estimate of maintenance cost are deterministic, i.e., known with certainty. This assumption, however, is invalid especially with estimates over a long time horizon of bridge life. In this study, we consider the risks associated with bridge deterioration and maintenance cost in determining the optimal maintenance plan. The decisions variables include the strategic choice of essential maintenance (such as silane treatment and cathodic protection), and the intervals between periodic maintenance. A ε‐constrained Particle Swarm Optimization algorithm is used to approximate the tradeoff between life‐cycle cost and performance indicators. During stochastic search for optimal solutions, Monte‐Carlo simulation is used to evaluate the impact of risks on the objective values, at an acceptance level of reliability. The proposed model can facilitate decision makers to select the compromised maintenance plan with a group of alternative choices, each of which leads to a different level of performance and life‐cycle cost. A numerical example is used to illustrate the proposed model.