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Routing for bridge inspecting robots using a metaheuristic genetic algorithm

Published: 19 July 2022 Publication History

Abstract

Deteriorating bridge infrastructure accounts for billions per year in inspection costs worldwide and recent advances in robotics and autonomy for bridge inspection can significantly decrease these costs. However, generating optimal tours for inspection robots to cover all members of a bridge truss maps to the well known but NP-hard Min-Max k-Chinese Postman arc-routing problem. We thus attack this problem with a new meta-heuristic genetic algorithm that quickly produces near-optimal balanced tours for k robots. Meta-heuristic genetic algorithm produced tour quality is statistically indistinguishable from best know results on common benchmarks. Scaling up to real-world bridge sizes, our genetic algorithm produces significantly better (15.24%) tours in a fraction of the time (0.05) compared to a prior genetic algorithm approach using a direct encoding. These results show the potential of our new approach for the broad class of arc-routing problems and specifically for quickly generating high-quality tours for robot-assisted real-world bridge inspection tasks.

References

[1]
Dino Ahr. Contributions to Multiple Postmen Problems. 2004. Publisher: Heidelberg University Library.
[2]
Dino Ahr and Gerhard Reinelt. New heuristics and lower bounds for the min-max k-chinese postman problem. In Rolf Möhring and Rajeev Raman, editors, Algorithms --- ESA 2002, pages 64--74, Berlin, Heidelberg, 2002. Springer Berlin Heidelberg.
[3]
Dino Ahr and Gerhard Reinelt. A tabu search algorithm for the min-max k-chinese postman problem. Computers & Operations Research, 33(12):3403 -- 3422, 2006. Part Special Issue: Recent Algorithmic Advances for Arc Routing Problems.
[4]
Dino Ahr and Gerhard Reinelt. A tabu search algorithm for the min-max k-Chinese postman problem. Computers & Operations Research, 33(12):3403--3422, December 2006.
[5]
S.K. Amponsah and S. Salhi. The investigation of a class of capacitated arc routing problems: The collection of garbage in developing countries. Waste Management, 24(7):711--721, 2004.
[6]
Corberán and Prins. Recent results on arc routing problems: an annotated bibliography. Networks, 56(1):50--69, 2010.
[7]
G. Fleury, P. Lacomme, and C. Prins. Evolutionary algorithms for stochastic arc routing problems. Lecture Notes in Computer Science, 3005:501--512, 2002.
[8]
Gianpaolo Ghiani, Francesca Guerriero, and Gennaro Improta. Waste collection in southern italy: Solution of a real-life arc routing problem. Int Trans Oper Res, 12(2):135--144, 2005.
[9]
B.L. Golden, J.S. Dearmon, and E.K. Baker. Computational experiments with algorithms for a class of routing problems. Computers & Operations Research, 10(1):47--59, 1983.
[10]
Nicholas Harris, Siming Liu, Sushil J. Louis, and Jim Hung La. A genetic algorithm for multi-robot routing in automated bridge inspection. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 369--370, Prague Czech Republic, July 2019. ACM.
[11]
Nicholas Harris, Sushil J. Louis, Jim Hung La, and Siming Liu. Genetic Algorithm Based Route Optimization for Robotic Bridge Inspection. Preprint submitted to Engineering Applications of Articial Intelligence, 2020.
[12]
Geir Hasle. Chapter 16: Arc Routing Applications in Newspaper Delivery, pages 371--395. Siam, 10 2013.
[13]
Lacomme, Prins, and Sevaux. A genetic algorithm for a bi-objective capacitated arc routing problem. Computers & Operations Research, 33(12):3473--3493, 2006.
[14]
Philippe Lacomme, Christian Prins, and Wahiba Ramdane-Cherif. Competitive memetic algorithms for arc routing problems. Annals of Operations Research, 131(1--4):159--185, 2004.
[15]
David Lattanzi and Gregory Miller. Review of robotic infrastructure inspection systems. Journal of Infrastructure Systems, 23(3):04017004, 2017.
[16]
L. Muyldermans, D. Cattrysse, D. Van Oudheusen, and Lotan T. Districting for salt spreading operations. European Journal of Operational Research, 139(3):521--532, 2002.
[17]
United States Department of Transportation. National bridge inventory - bridge inspection - safety - bridges & structrues. http://www.fhwa.dot.gov/bridge/nbi.cfm, 2019. Accessed: 12/19/16.

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cover image ACM Conferences
GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion
July 2022
2395 pages
ISBN:9781450392686
DOI:10.1145/3520304
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Publication History

Published: 19 July 2022

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Author Tags

  1. bridge inspection
  2. combinatorial optimization
  3. genetic algorithms
  4. metaheuristics
  5. routing and layout

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