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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 9, 2019.
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.
Calista Elysia, Michelle Hartanto and Ditdit Nugeraha Utama, “Hybrid Latin-Hyper-Cube-Hill-Climbing Method for Optimizing: Experimental Testing” International Journal of Advanced Computer Science and Applications(IJACSA), 10(9), 2019. http://dx.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},
doi = {10.14569/IJACSA.2019.0100955},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100955},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {9},
author = {Calista Elysia and Michelle Hartanto and Ditdit Nugeraha Utama}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.