An effective multi-objective approach to prioritisation of sewer pipe inspection

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@Article{Berardi:2009:WST,
  author =       "L. Berardi and O. Giustolisi and D. A. Savic and 
                 Z. Kapelan",
  title =        "An effective multi-objective approach to
                 prioritisation of sewer pipe inspection",
  journal =      "Water Science \& Technology",
  year =         "2009",
  volume =       "60",
  number =       "4",
  pages =        "841--850",
  keywords =     "genetic algorithms, genetic programming, EPR, decision
                 support, multi-objective optimisation, pipe inspection,
                 prioritisation, sewer, CCTV",
  DOI =          "doi:10.2166/wst.2009.432",
  size =         "10 pages",
  abstract =     "The first step in the decision making process for
                 proactive sewer rehabilitation is to assess the
                 condition of conduits. In a risk-based decision context
                 the set of sewers to be inspected first should be
                 identified based on the trade-off between the risk of
                 failures and the cost of inspections. In this paper the
                 most effective inspection works are obtained by solving
                 a multi-objective optimisation problem where the total
                 cost of the survey programme and the expected cost of
                 emergency repairs subsequent to blockages and collapses
                 are considered simultaneously. A multi-objective
                 genetic algorithm (MOGA) is used to identify a set of
                 Pareto-optimal inspection programmes. Regardless of the
                 proven effectiveness of the genetic-algorithm approach,
                 the scrutiny of MOGA-based inspection strategies shows
                 that they can differ significantly from each other,
                 even when having comparable costs. A post-processing of
                 MOGA solutions is proposed herein, which allows
                 priority to be assigned to each survey intervention.
                 Results are of practical relevance for decision makers,
                 as they represent the most effective sequence of
                 inspection works to be carried out based on the
                 available funds. The proposed approach is demonstrated
                 on a real large sewer system in the UK.",
  notes =        "Papers using GP related results

                 WST, IWA Publishing

                 Civil and Environmental Engineering Department,
                 Technical University of Bari, via Orabona 4, 70125,
                 Bari, Italy E-mail: l.berardi@poliba.it;
                 o.giustolisi@poliba.it Centre for Water Systems, School
                 of Engineering, Computing and Mathematics, University
                 of Exeter, North Park Road, Exeter EX4 4QF, UK E-mail:
                 d.savic@exeter.ac.uk; z.kapelan@exeter.ac.uk",
}

Genetic Programming entries for Luigi Berardi Orazio Giustolisi Dragan Savic Zoran Kapelan

Citations