TY - GEN
T1 - An Adaptive Intelligent Water Drops Algorithm for Set Covering Problem
AU - CRAWFORD LABRIN, BRODERICK
AU - SOTO DE GIORGIS, RICARDO JAVIER
AU - Astorga, Gino
AU - Lemus-Romani, Jose
AU - Misra, Sanjay
AU - Rubio, Jose Miguel
N1 - Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/7
Y1 - 2019/7
N2 - Today, natural resources are more scarce than ever, so we must make good use of them. To achieve this goal, we can use metaheuristic optimization tools as an alternative to achieve good results in a reasonable amount of time. The present work focuses on the use of adaptive techniques to facilitate the use of this type of tool to obtain good functional parameters. We use a constructive metaheuristic algorithm called Intelligent Water Drops to solve the set covering problem. To demonstrate the efficiency of the proposed method, the obtained results were compared with the standard version using the same initial configuration for both algorithms. Additionally, the Kolmogorov-Smirnov-Lilliefors, Wilcoxon signed-rank and Violin chart tests were applied to statistically validate the results, which showed that metaheuristics with autonomous search have a better behavior than do standard algorithms.
AB - Today, natural resources are more scarce than ever, so we must make good use of them. To achieve this goal, we can use metaheuristic optimization tools as an alternative to achieve good results in a reasonable amount of time. The present work focuses on the use of adaptive techniques to facilitate the use of this type of tool to obtain good functional parameters. We use a constructive metaheuristic algorithm called Intelligent Water Drops to solve the set covering problem. To demonstrate the efficiency of the proposed method, the obtained results were compared with the standard version using the same initial configuration for both algorithms. Additionally, the Kolmogorov-Smirnov-Lilliefors, Wilcoxon signed-rank and Violin chart tests were applied to statistically validate the results, which showed that metaheuristics with autonomous search have a better behavior than do standard algorithms.
KW - Autonomous Search
KW - Combinatorial Optimization
KW - Metaheuristics
UR - http://www.scopus.com/inward/record.url?scp=85077821445&partnerID=8YFLogxK
U2 - 10.1109/ICCSA.2019.000-6
DO - 10.1109/ICCSA.2019.000-6
M3 - Conference contribution
AN - SCOPUS:85077821445
T3 - Proceedings - 2019 19th International Conference on Computational Science and Its Applications, ICCSA 2019
SP - 39
EP - 45
BT - Proceedings - 2019 19th International Conference on Computational Science and Its Applications, ICCSA 2019
A2 - Misra, Sanjay
A2 - Gervasi, Osvaldo
A2 - Murgante, Beniamino
A2 - Stankova, Elena
A2 - Korkhov, Vladimir
A2 - Torre, Carmelo
A2 - Rocha, Ana Maria A. C.
A2 - Taniar, David
A2 - Apduhan, Bernady O.
A2 - Tarantino, Eufemia
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 July 2019 through 4 July 2019
ER -