Algorithms for bottom-up maintenance optimisation for heterogeneous infrastructure systems

Abstract

This paper presents a methodology for maintenance optimisation for heterogeneous infrastructure systems, i.e., systems composed of multiple facilities with different characteristics such as environments, materials, and deterioration processes. We present a bottom-up approach: facility-level optimal maintenance policies are first found; these policies are then combined with budget constraints in the system-level optimisation. In the first step, optimal and near-optimal maintenance policies for each facility are found and used as inputs for the system-level optimisation. In the second step, the problem is formulated as a constrained combinatorial optimisation problem, where the best combination of facility-level optimal and near-optimal solutions is identified. Two heuristics, pattern search heuristic (PSH) and evolutionary algorithm (EA), are adopted to solve the combinatorial optimisation problem. Their performance is evaluated using a hypothetical system of pavement sections. Comparison result with real optimal solutions for 20 facilities showed that both algorithms give near-optimal solutions (within less than 0.1% difference from the optimal solution) in 978 (PSH) and 966 (EA) cases out of 1000 executions. The EA performs better in terms of processing time than the PSH. Numerical experiments show the potential of the proposed algorithms to solve the maintenance optimisation problem for realistic heterogeneous systems.