article · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2018

Local intensity in memetic algorithm

Zhiwei Zeng, Xiao-Min Hu, Min Li, Yu Luo

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Abstract

he research in capacitated arc routing problems (CARPs) is getting more and more attention for its wide applications in reality. Memetic algorithms (MAs) are promising in solving CARPs, but the intensity of local search (LS) in MAs should adapt to the evolution of the population for achieving the maximal effectiveness. In this paper, a novel MA based on adaptive adjustment of LS intensity (LIMA) is proposed. LIMA dynamically adjusts the probability of LS according to the distance between the individual of the population and the solution lower bound for further deepening the LS depth of potential solutions. It makes the algorithm spend as much time as possible on more potential solutions, so as to shorten the computation time and speed up the convergence. Experimental results show that LIMA has faster convergence speed and better global search ability than traditional MAs. Adaptively tuning the LS intensity of a MA has high potential for solving complex problems.1

Cite this paper

APA 7

Zeng, Z., Hu, X.-M., Li, M., & Luo, Y. (2018). Local intensity in memetic algorithm. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 153–154. https://doi.org/10.1145/3205651.3205677

MLA 9

Zeng, Zhiwei, et al. “Local intensity in memetic algorithm.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018, pp. 153–54, https://doi.org/10.1145/3205651.3205677.

Chicago

Zeng, Zhiwei, Xiao-Min Hu, Min Li, and Yu Luo. 2018. “Local intensity in memetic algorithm.” Proceedings of the Genetic and Evolutionary Computation Conference Companion: 153–54. https://doi.org/10.1145/3205651.3205677.

Harvard

Zeng, Z. et al. (2018) ‘Local intensity in memetic algorithm’, Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 153–154. Available at: https://doi.org/10.1145/3205651.3205677.

BibTeX

@article{zeng2018local,
  title = {{Local intensity in memetic algorithm}},
  author = {Zeng, Zhiwei and Hu, Xiao-Min and Li, Min and Luo, Yu},
  journal = {Proceedings of the Genetic and Evolutionary Computation Conference Companion},
  pages = {153--154},
  year = {2018},
  doi = {10.1145/3205651.3205677}
}

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