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Research Article | Open Access |

Hybrid Latin-Hyper-Cube-Hill-Climbing Method for Optimizing: Experimental Testing

Author 1: Calista Elysia Author 2: Michelle Hartanto Author 3: Ditdit Nugeraha Utama
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 10, No. 9 · Published 2019

DOI: https://doi.org/10.14569/IJACSA.2019.0100955

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Abstract

A noticeable objective of this work is to experiment and test an optimization problem through comparing hill-climbing method with a hybrid method combining hill-climbing and Latin-hyper-cube. These two methods are going to be tested operating the same data-set in order to get the comparison result for both methods. The result shows that the hybrid model has a better performance than hill-climbing. Based on the number of global optimum value occurrence, the hybrid model outperformed 7.6% better than hill-climbing, and produced more stable average global optimum value. However, the model has a little longer running time due to a genuine characteristic of the model itself.

Keywords

Hill-climbing Latin-hyper-cube optimization

How to Cite this Article

Elysia, C., Hartanto, M., & Utama, D. N. (2019). Hybrid Latin-Hyper-Cube-Hill-Climbing Method for Optimizing: Experimental Testing. International Journal of Advanced Computer Science and Applications, 10(9). https://doi.org/10.14569/IJACSA.2019.0100955

Elysia, Calista, et al.. "Hybrid Latin-Hyper-Cube-Hill-Climbing Method for Optimizing: Experimental Testing." International Journal of Advanced Computer Science and Applications, vol. 10, no. 9, 2019, https://doi.org/10.14569/IJACSA.2019.0100955.

@article{Elysia2019,
  title     = {Hybrid Latin-Hyper-Cube-Hill-Climbing Method for Optimizing: Experimental Testing},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {9},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Calista Elysia and Michelle Hartanto and Ditdit Nugeraha Utama},
  doi       = {10.14569/IJACSA.2019.0100955},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100955}
}

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