A novel Grouping Coral Reefs Optimization algorithm for optimal mobile network deployment problems under electromagnetic pollution and capacity control criteria

2016 ◽  
Vol 55 ◽  
pp. 388-402 ◽  
Author(s):  
Sancho Salcedo-Sanz ◽  
Pilar García-Díaz ◽  
Javier Del Ser ◽  
Miren Nekane Bilbao ◽  
José Antonio Portilla-Figueras
2014 ◽  
Vol 24 ◽  
pp. 239-248 ◽  
Author(s):  
S. Salcedo-Sanz ◽  
P. García-Díaz ◽  
J.A. Portilla-Figueras ◽  
J. Del Ser ◽  
S. Gil-López

2021 ◽  
Vol 286 ◽  
pp. 112250
Author(s):  
Mohammad Emami ◽  
Sara Nazif ◽  
Sayed-Farhad Mousavi ◽  
Hojat Karami ◽  
Andre Daccache

2020 ◽  
Vol 55 ◽  
pp. 100688 ◽  
Author(s):  
L. Garcia-Hernandez ◽  
L. Salas-Morera ◽  
C. Carmona-Muñoz ◽  
A. Abraham ◽  
S. Salcedo-Sanz

2015 ◽  
Vol 75 ◽  
pp. 93-101 ◽  
Author(s):  
S. Salcedo-Sanz ◽  
A. Pastor-Sánchez ◽  
J. Del Ser ◽  
L. Prieto ◽  
Z.W. Geem

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
S. Salcedo-Sanz ◽  
J. Del Ser ◽  
I. Landa-Torres ◽  
S. Gil-López ◽  
J. A. Portilla-Figueras

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems.


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