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Memetic Computing

, Volume 10, Issue 1, pp 81–102 | Cite as

Quantum-Inspired Immune Clonal Algorithm for solving large-scale capacitated arc routing problems

  • Ronghua Shang
  • Bingqi Du
  • Kaiyun Dai
  • Licheng Jiao
  • Amir M. Ghalamzan Esfahani
  • Rustam Stolkin
Regular Research Paper

Abstract

In this paper, we present an approach to Large-Scale CARP called Quantum-Inspired Immune Clonal Algorithm (QICA-CARP). This algorithm combines the feature of artificial immune system and quantum computation ground on the qubit and the quantum superposition. We call an antibody of population quantum bit encoding, in QICA-CARP. For this encoding, to control the population with a high probability evolution towards a good schema we use the information on the current optimal antibody. The mutation strategy of quantum rotation gate accelerates the convergence of the original clone operator. Moreover, quantum crossover operator enhances the exchange of information and increases the diversity of the population. Furthermore, it avoids falling into local optimum. We also use the repair operator to amend the infeasible solutions to ensure the diversity of solutions. This makes QICA-CARP approximating the optimal solution. We demonstrate the effectiveness of our approach by a set of experiments and by Comparing the results of our approach with ones obtained with the RDG-MAENS and RAM using different test sets. Experimental results show that QICA-CARP outperforms other algorithms in terms of convergence rate and the quality of the obtained solutions. Especially, QICA-CARP converges to a better lower bound at a faster rate illustrating that it is suitable for solving large-scale CARP.

Keywords

Large-scale CARP Quantum rotation gate Quantum crossover operator The repair operator 

Notes

Acknowledgements

We would like to express our sincere appreciation to the editors and the anonymous reviewers for their insightful comments, which have greatly helped us in improving the quality of the paper.

References

  1. 1.
    Shang RH, Wang J, Jiao LC, Wang YY (2014) An improved decomposition-based memetic algorithm for multi-objective capacitated arc routing problem. Appl Soft Comput 19(1):343–361CrossRefGoogle Scholar
  2. 2.
    Wen XZ, Shao L, Xue Y, Fang W (2015) A rapid learning algorithm for vehicle classification. Inform Sci 295(1):395–406CrossRefGoogle Scholar
  3. 3.
    Mei Y, Tang K, Yao X (2011) Decomposition-based memetic algorithm for multi-objective capacitated arc routing problems. IEEE Trans Evolut Comput 15(2):151–165CrossRefGoogle Scholar
  4. 4.
    Shen J, Tan HW, Wang J, Wang JW, Lee SY (2015) A novel routing protocol providing good transmission reliability in underwater sensor networks. J Internet Technol 16(1):171–178Google Scholar
  5. 5.
    Golden BL, DeArmon JS, Baker EK (1983) Computational experiments with algorithms for a class of routing problems. Comput Oper Res 10(1):47–59MathSciNetCrossRefGoogle Scholar
  6. 6.
    Ulusoy G (1985) The fleet size and mix problem for capacitated arc routing. Eur J Oper Res 22(3):329–337MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Pearn WL (1991) Augment-insert algorithms for the capacitated arc routing problem. Comput Oper Res 18(2):189–198MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Pearn WL (1989) Approximate solutions for the capacitated arc routing problem. Comput Oper Res 16(6):589–600MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Tan KC, Khor EF, Lee TH (2005) Multi-objective evolutionary algorithms and applications. Springer, BerlinzbMATHGoogle Scholar
  10. 10.
    Xia ZH, Wang XH, Sun XM, Wang Q (2015) A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data. IEEE Trans Parallel Distrib Syst 27(2):340–352CrossRefGoogle Scholar
  11. 11.
    Reed M, Yiannakou A, Evering R (2014) An ant colony algorithm for the multi-compartment vehicle routing problem. Appl Soft Comput 15:169–176CrossRefGoogle Scholar
  12. 12.
    Glover F, Laguna M (1997) Tabu search. Kluwer Academic, BostonCrossRefzbMATHGoogle Scholar
  13. 13.
    Mei Y, Tang K, Yao X (2011) A memetic algorithm for periodic capacitated arc routing problem. IEEE Trans Syst Man Cybern B 41(6):1654–1667CrossRefGoogle Scholar
  14. 14.
    Zheng YH, Jeon B, Xu DH, Wu QMJ, Zhang H (2015) Image segmentation by generalized hierarchical fuzzy C-means algorithm. J Intell Fuzzy Syst 28(2):961–973Google Scholar
  15. 15.
    Goldbarg MC, Asconavieta PH (2012) Memetic algorithm for the traveling car renter problem: an experimental investigation. Memet Comput 4(2):89–108CrossRefGoogle Scholar
  16. 16.
    Feng L, Ong YS, Tan AH, Tsang IW (2015) Memes as building blocks: a case study on evolutionary optimization+transfer learning for routing problems. Memet Comput 7(3):159–180CrossRefGoogle Scholar
  17. 17.
    Hertz A, Laporte G, Mittaz M (2000) A tabu search heuristic for the capacitated arc routing problem. Oper Res 48(1):129–135MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Hertz A, Mittaz M (2001) A variable neighborhood descent algorithm for the undirected capacitated arc routing problem. Trans Sci 35(4):425–434CrossRefzbMATHGoogle Scholar
  19. 19.
    Lacomme P, Prins C, Ramdane-Cherif W (2004) Competitive memetic algorithms for arc routing problem. Ann Oper Res 131(1–4):159–185MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Shang RH, Jiao LC, Liu F (2012) A novel immune clonal algorithm for MO problems. IEEE Trans Evolut Comput 16(1):35–49CrossRefGoogle Scholar
  21. 21.
    Gong M, Liu C, Jiao L, Cheng G (2010) Hybrid immune algorithm with Lamarckian local search for multi-objective optimization. Memet Comput 2(1):47–67CrossRefGoogle Scholar
  22. 22.
    Tang K, Mei Y, Yao X (2009) Memetic algorithm with extended neighborhood search for capacitated arc routing problems. IEEE Trans Evolut Comput 13(5):1151–1166CrossRefGoogle Scholar
  23. 23.
    Mei Y, Li XD, Yao X (2014) Cooperative co-evolution with route distance grouping for large-scale capacitated arc routing problems. IEEE Trans Evolut Comput 18(3):435–449CrossRefGoogle Scholar
  24. 24.
    Tonda A, Lutton E, Squillero G (2012) A benchmark for cooperative coevolution. Memet Comput 4(4):263–277CrossRefGoogle Scholar
  25. 25.
    Nguyen ML, Hui SC, Fong ACM (2012) Divide-and-conquer memetic algorithm for online multi-objective test paper generation. Memet Comput 4(1):33–47CrossRefGoogle Scholar
  26. 26.
    Shang RH, Wang YY, Wang J, Jiao LC, Wang S, Qi LP (2014) A multi-population cooperative coevolutionary algorithm for multi-objective capacitated arc routing problem. Inform Sci 27(7):609–642MathSciNetCrossRefzbMATHGoogle Scholar
  27. 27.
    Dijkstra E (1959) A note on two problems in connexion with graphs. Number Math 1(1):269–271MathSciNetCrossRefzbMATHGoogle Scholar
  28. 28.
    Marinaki M, Marinakis Y (2015) A hybridization of clonal selection algorithm with iterated local search and variable neighborhood search for the feature selection problem. Memet Comput 7(3):181–201CrossRefGoogle Scholar
  29. 29.
    De Castro LN, Von Zuben FJ (2002) Learning and optimization using the clonal selection principle. IEEE Trans Evolut Comput 6(3):239–251CrossRefGoogle Scholar
  30. 30.
    Jiao LC, Li YY, Gong MG, Zhang XR (2008) Quantum-inspired immune clonal algorithm for global optimization. IEEE Trans Syst Man Cybern B (Cybernetics) 38(5):1234–1253CrossRefGoogle Scholar
  31. 31.
    Li YY, Jiao LC (2005) Quantum-inspired immune clonal algorithm. In: Proceedings of the 4th international conference on artificial immune systems, Banff, pp 304–317Google Scholar
  32. 32.
    Handa H, Chapman L, Yao X (2006) Robust route optimization for gritting/salting trucks: a CERCIA experience. IEEE Comput Intell Mag 1(1):6–9CrossRefGoogle Scholar
  33. 33.
    Mei Y, Tang K, Yao X (2009) A global repair operator for capacitated arc routing problem. IEEE Trans Syst Man Cyber B 39(3):723–734CrossRefGoogle Scholar
  34. 34.
    Wang ZR, Jin HY, Tian MM (2015) Rank-based memetic algorithm for capacitated arc routing problems. Appl Soft Comput 37:572–584CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Ronghua Shang
    • 1
  • Bingqi Du
    • 1
  • Kaiyun Dai
    • 1
  • Licheng Jiao
    • 1
  • Amir M. Ghalamzan Esfahani
    • 2
  • Rustam Stolkin
    • 2
  1. 1.Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of ChinaXidian UniversityXi’anChina
  2. 2.Extreme Robotics LabUniversity of BirminghamEdgbaston, BirminghamUK

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