Bi-objective modeling approach for repairing multiple feature infrastructure systems

A bi-objective decision aid model for planning long-term maintenance of infrastructure systems is presented, oriented to interventions on their constituent elements, with two upgrade levels possible for each element (partial/full repairs). The model aims at maximizing benefits and minimizing costs, and its novelty is taking into consideration, and combining, the system/element structure, volume discounts, and socioeconomic factors. The model is tested with field data from 229 sidewalks (systems) and compared to two simpler repair policies, of allowing only partial or full repairs. Results show that the efficiency gains are greater in the lower mid-range budget region. The proposed modeling approach is an innovative tool to optimize cost/benefits for the various repair options and analyze the respective trade-offs.info:eu-repo/semantics/publishedVersio

Stochastics and Statistics An improved algorithm for the computation of the optimal repair/replacement policy under general repairs

Abstract We consider a system which deteriorates with age and may experience a failure at any time instant. On failure, the system may be replaced or repaired. The repair can partially reset the failure intensity of the unit. Under a suitable cost structure it has been proved in the literature that the average-cost optimal policy is of control-limit type, i.e. it conducts a replacement if and only if, on the nth failure, the real age of the system is greater than or equal to a critical value. We develop an efficient special-purpose policy iteration algorithm that generates a sequence of improving control-limit policies. The value determination step of the algorithm is based on the embedding technique. There is strong numerical evidence that the algorithm converges to the optimal policy