An Improved Genetic Programming Hyper-Heuristic for the Uncertain Capacitated Arc Routing Problem

  • Jordan MacLachlanEmail author
  • Yi Mei
  • Juergen Branke
  • Mengjie Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11320)


This paper uses a Genetic Programming Hyper-Heuristic (GPHH) to evolve routing policies for the Uncertain Capacitated Arc Routing Problem (UCARP). Given a UCARP instance, the GPHH evolves feasible solutions in the form of decision making policies which decide the next task to serve whenever a vehicle completes its current service. Existing GPHH approaches have two drawbacks. First, they tend to generate small routes by routing through the depot and refilling prior to the vehicle being fully loaded. This usually increases the total cost of the solution. Second, existing GPHH approaches cannot control the extra repair cost incurred by a route failure, which may result in higher total cost. To address these issues, this paper proposes a new GPHH algorithm with a new No-Early-Refill filter to prevent generating small routes, and a novel Flood Fill terminal to better handle route failures. Experimental studies show that the newly proposed GPHH algorithm significantly outperforms the existing GPHH approaches on the Ugdb and Uval benchmark datasets. Further analysis has verified the effectiveness of both the new filter and terminal.


Arc routing Hyper-heuristic Genetic programming 


  1. 1.
    Amponsah, S., Salhi, S.: The investigation of a class of capacitated arc routing problems: the collection of garbage in developing countries. Waste Manag. 24(7), 711–721 (2004)CrossRefGoogle Scholar
  2. 2.
    Branke, J., Nguyen, S., Pickardt, C.W., Zhang, M.: Automated design of production scheduling heuristics: a review. IEEE Trans. Evol. Comput. 20(1), 110–124 (2016)CrossRefGoogle Scholar
  3. 3.
    Burke, E.K., Hyde, M., Kendall, G., Woodward, J.: A genetic programming hyper-heuristic approach for evolving 2-D strip packing heuristics. IEEE Trans. Evol. Comput. 14(6), 942–958 (2010)CrossRefGoogle Scholar
  4. 4.
    Christiansen, C., Lysgaard, J., Wøhlk, S.: A branch-and-price algorithm for the capacitated arc routing problem with stochastic demands. Oper. Res. Lett. 37(6), 392–398 (2009)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Defryn, C., Sörensen, K., Cornelissens, T.: The selective vehicle routing problem in a collaborative environment. Eur. J. Oper. Res. 250(2), 400–411 (2015)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Eglese, R.W., Li, L.Y.O.: A tabu search based heuristic for arc routing with a capacity constraint and time deadline. In: Osman, I.H., Kelly, J.P. (eds.) Meta-Heuristics: Theory and Applications, pp. 633–649. Springer, Boston (1996). Scholar
  7. 7.
    Fleury, G., Lacomme, P., Prins, C., Ramdane-Chérif, W.: Improving robustness of solutions to arc routing problems. J. Oper. Res. Soc. 56(5), 526–538 (2005)CrossRefGoogle Scholar
  8. 8.
    Golden, B., Dearmon, J., Baker, E.: Computational experiments with algorithms for a class of routing problems. Comput. Oper. Res. 10, 47–59 (1983)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Golden, B., Wong, R.: Capacitated arc routing problems. Networks 11(3), 305–315 (1981)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Handa, H., Chapman, L., Yao, X.: Dynamic salting route optimisation using evolutionary computation. In: IEEE Congress on Evolutionary Computation, pp. 158–165 (2005)Google Scholar
  11. 11.
    Handa, H., Chapman, L., Yao, X.: Robust route optimization for gritting/salting trucks: a CERCIA experience. IEEE Comput. Intell. Mag. 1(1), 6–9 (2006)CrossRefGoogle Scholar
  12. 12.
    Hertz, A., Laporte, G., Mittaz, M.: A tabu search heuristic for the capacitated arc routing problem. Oper. Res. 48, 129–135 (2000)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Lacomme, P., Prins, C., Ramdane-Cherif, W.: Competitive memetic algorithms for arc routing problems. Ann. Oper. Res. 131(1), 159–185 (2004)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Liu, Y., Mei, Y., Zhang, M., Zhang, Z.: Automated heuristic design using genetic programming hyper-heuristic for uncertain capacitated arc routing problem. In: Proceedings of GECCO, pp. 290–297. ACM (2017)Google Scholar
  15. 15.
    Mei, Y., Tang, K., Yao, X.: Improved memetic algorithm for capacitated arc routing problem. In: IEEE Congress on Evolutionary Computation, pp. 1699–1706 (2009)Google Scholar
  16. 16.
    Mei, Y., Tang, K., Yao, X.: Capacitated arc routing problem in uncertain environments. In: IEEE Congress on Evolutionary Computation, pp. 1–8 (2010)Google Scholar
  17. 17.
    Mei, Y., Zhang, M.: Genetic programming hyper-heuristic for multi-vehicle uncertain capacitated arc routing problem. In: ACM Genetic and Evolutionary Computation Conference (GECCO) (2017)Google Scholar
  18. 18.
    Nguyen, S., Mei, Y., Zhang, M.: Genetic programming for production scheduling: a survey with a unified framework. Complex Intell. Syst. 3(1), 41–66 (2017)CrossRefGoogle Scholar
  19. 19.
    Speranza, M., Fernandez, E., Roca-Riu, M.: The shared customer collaboration vehicle routing problem. Eur. J. Oper. Res. 265(3), 1078–1093 (2016)MathSciNetzbMATHGoogle Scholar
  20. 20.
    Tsutsui, S., Wilson, G.: Solving capacitated vehicle routing problems using edge histogram based sampling algorithms. In: Proceedings of the 2004 Congress on Evolutionary Computation, vol. 1, pp. 1150–1157 (2004)Google Scholar
  21. 21.
    Ulusoy, G.: The fleet size and mix problem for capacitated arc routing. Eur. J. Oper. Res. 22(3), 329–337 (1985)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Wang, J., Tang, K., Lozano, J.A., Yao, X.: Estimation of the distribution algorithm with a stochastic local search for uncertain capacitated arc routing problems. IEEE Trans. Evol. Comput. 20(1), 96–109 (2016)CrossRefGoogle Scholar
  23. 23.
    Wang, J., Tang, K., Yao, X.: A memetic algorithm for uncertain capacitated arc routing problems. In: 2013 IEEE Workshop on Memetic Computing, pp. 72–79 (2013)Google Scholar
  24. 24.
    Weise, T., Devert, A., Tang, K.: A developmental solution to (dynamic) capacitated arc routing problems using genetic programming. In: Proceedings of GECCO, pp. 831–838. ACM (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jordan MacLachlan
    • 1
    Email author
  • Yi Mei
    • 1
  • Juergen Branke
    • 2
  • Mengjie Zhang
    • 1
  1. 1.Victoria University of WellingtonKelburnNew Zealand
  2. 2.The University of WarwickCoventryUK

Personalised recommendations