Maintenance optimization for heterogeneous infrastructure systems: Evolutionary algorithms for bottom-up methods

Hwasoo Yeo, Yoonjin Yoon, Samer Madanat

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter presents a methodology for maintenance optimization for heterogeneous infrastructure systems, i.e., systems composed of multiple facilities with different characteristics such as environments, materials and deterioration processes. We present a two-stage bottom-up approach. In the first step, optimal and near-optimal maintenance policies for each facility are found and used as inputs for the system-level optimization. In the second step, the problem is formulated as a constrained combinatorial optimization problem, where the best combination of facility-level optimal and near-optimal solutions is identified. An Evolutionary Algorithm (EA) is adopted to solve the combinatorial optimization problem. Its performance is evaluated using a hypothetical system of pavement sections. We find that a near-optimal solution (within less than 0.1% difference from the optimal solution) can be obtained in most cases. Numerical experiments show the potential of the proposed algorithm to solve the maintenance optimization problem for realistic heterogeneous systems.

Original languageEnglish (US)
Title of host publicationSustainable and Resilient Critical Infrastructure Systems
Subtitle of host publicationSimulation, Modeling, and Intelligent Engineering
PublisherSpringer Berlin Heidelberg
Pages185-199
Number of pages15
ISBN (Print)9783642114045
DOIs
StatePublished - Dec 1 2010

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Yeo, H., Yoon, Y., & Madanat, S. (2010). Maintenance optimization for heterogeneous infrastructure systems: Evolutionary algorithms for bottom-up methods. In Sustainable and Resilient Critical Infrastructure Systems: Simulation, Modeling, and Intelligent Engineering (pp. 185-199). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-11405-2_7