Abstract
This paper introduces a novel parallel immune-inspired algorithm based on recent developments in the understanding of the germinal centre reaction in the immune system. Artificial immune systems are relatively new randomised search heuristics and work on parallelising them is still in its infancy. We compare our algorithm with a parallel implementation of a simple multi-objective evolutionary algorithm on benchmark instances of the set cover problem taken from the OR-library. We show that our algorithm finds feasible solutions faster than the evolutionary algorithm using less parameters and communication effort.
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Beasley, J.E.: OR-library: Distributing test problems by electronic mail. The Journal of the Operational Research Society 41(11), 1069–1072 (1990), https://files.nyu.edu/jeb21/public/jeb/info.html
Caprara, A., Toth, P., Fischetti, M.: Algorithms for the set covering problem. Annals of Operations Research 98(1-4), 353–371 (2000)
De Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer (2002)
Deb, K.: Multi-objective Optimization Using Evolutionary Algorithms. Wiley-Blackwell (2001)
Friedrich, T., He, J., Hebbinghaus, N., Neumann, F., Witt, C.: Approximating covering problems by randomized search heuristics using multi-objective models. Evolutionary Computation 18(4), 617–633 (2010)
Giel, O., Wegener, I.: Evolutionary algorithms and the maximum matching problem. In: Alt, H., Habib, M. (eds.) STACS 2003. LNCS, vol. 2607, pp. 415–426. Springer, Heidelberg (2003)
Greensmith, J.: The Dendritic Cell Algorithm. PhD thesis, University of Nottingham (2007), http://www.cs.nott.ac.uk/~jqg/thesis.pdf
Grossman, T., Wool, A.: Computational experience with approximation algorithms for the set covering problem. European Journal of Operational Research 101(1), 81–92 (1997)
Joshi, A.: Design of a parallel immune algorithm based on the germinal center reaction. In: Proc of GECCO Companion, pp. 1671–1674. ACM (2013)
Kim, J., Bentley, P.J.: Towards an artificial immune system for network intrusion detection: An investigation of clonal selection with a negative selection operator. In: Proc. of CEC, vol. 2, pp. 1244–1252. IEEE Press (2002)
Luque, G., Alba, E.: Parallel Genetic Algorithms: Theory and Real World Applications. Springer (2011)
Mambrini, A., Sudholt, D., Yao, X.: Homogeneous and heterogeneous island models for the set cover problem. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds.) PPSN 2012, Part I. LNCS, vol. 7491, pp. 11–20. Springer, Heidelberg (2012)
Murphy, K.: Janeway’s Immunobiology. Garland Science (2011)
Musliu, N.: Local search algorithm for unicost set covering problem. In: Ali, M., Dapoigny, R. (eds.) IEA/AIE 2006. LNCS (LNAI), vol. 4031, pp. 302–311. Springer, Heidelberg (2006)
Sim, K., Hart, E., Paechter, B.: A lifelong learning hyper-heuristic method for bin packing. Evolutionary Computation (to appear, 2014), http://dx.doi.org/10.1162/EVCO_a_00121
Zhang, Y., Meyer-Hermann, M., George, L.A., Figge, M.T., Khan, M., Goodall, M., Young, S.P., Reynolds, A., Falciani, F., Waisman, A., Notley, C.A., Ehrenstein, M.R., Kosco-Vilbois, M., Toellner, K.-M.: Germinal center B cells govern their own fate via antibody feedback. The Journal of Experimental Medicine 210(3), 457–464 (2013)
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Joshi, A., Rowe, J.E., Zarges, C. (2014). An Immune-Inspired Algorithm for the Set Cover Problem. In: Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (eds) Parallel Problem Solving from Nature – PPSN XIII. PPSN 2014. Lecture Notes in Computer Science, vol 8672. Springer, Cham. https://doi.org/10.1007/978-3-319-10762-2_24
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DOI: https://doi.org/10.1007/978-3-319-10762-2_24
Publisher Name: Springer, Cham
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