An Improved Genetic Programming Hyper-Heuristic for the Uncertain Capacitated Arc Routing Problem
Conference paper
First Online:
- 6 Citations
- 1.3k Downloads
Abstract
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.
Keywords
Arc routing Hyper-heuristic Genetic programmingReferences
- 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.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.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.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.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.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). https://doi.org/10.1007/978-1-4613-1361-8_38CrossRefzbMATHGoogle Scholar
- 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.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.Golden, B., Wong, R.: Capacitated arc routing problems. Networks 11(3), 305–315 (1981)MathSciNetCrossRefGoogle Scholar
- 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.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.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.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.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.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.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.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.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.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.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.Ulusoy, G.: The fleet size and mix problem for capacitated arc routing. Eur. J. Oper. Res. 22(3), 329–337 (1985)MathSciNetCrossRefGoogle Scholar
- 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.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.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