Dr. Carlos Camacho Gómez

@article{PEREZARACIL2021100958,

title = {Memetic coral reefs optimization algorithms for optimal geometrical design of submerged arches},

author = {Jorge Pérez-Aracil and C. Camacho-Gómez and A. M. Hernández-Díaz and E. Pereira and David Camacho and Sancho Salcedo-Sanz},

url = {https://www.sciencedirect.com/science/article/pii/S2210650221001206},

doi = {https://doi.org/10.1016/j.swevo.2021.100958},

issn = {2210-6502},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Swarm and Evolutionary Computation},

volume = {67},

pages = {100958},

abstract = {This paper deals with the geometrically nonlinear analysis of submerged arches by means of memetic Coral Reefs Optimization algorithms. The classic design of submerged arches is only focused on calculating the bending stress-less shape (funicular shape) of the structure. Nevertheless, recent works show that this funicular shape can be approached by using a parametric family curve, which also allows a multi-variable optimization of the arch’s geometry. Using this novel parametric set of curves, we propose a new Coral Reefs Optimization (CRO) algorithm based on a memetic approach to tackle the geometrically nonlinear design of submerged arches. Specifically, the proposed CRO approaches have been tested with different search procedures as exploration operators, and we also test a multi-method version of the algorithm, the Coral Reefs Optimization with Substrate Layers (CRO-SL), which considers several search procedures within the same evolutionary population. A local search to improve the solutions has been considered in all cases, to obtain powerful memetic operators for this problem. It is also shown how the different memetic versions of the CRO (specially those involving multi-methods and Differential Evolution search procedures), together with the parametric encoding, are able to obtain nearly-optimal geometries for underwater installations. The performance of the proposed algorithm has been compared with state-of-the-art algorithms for optimization: L-SHADE and HCLPSO. Statistical tests have carried out with the aim of comparing the results. It is shown that there is not significant differences between the proposed results by the three algorithms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SALCEDOSANZ2018434,

title = {Efficient fractal-based mutation in evolutionary algorithms from iterated function systems},

author = {Sancho Salcedo-Sanz and A. Aybar-Ruíz and C. Camacho-Gómez and E. Pereira},

url = {https://www.sciencedirect.com/science/article/pii/S1007570417302915},

doi = {https://doi.org/10.1016/j.cnsns.2017.08.010},

issn = {1007-5704},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Communications in Nonlinear Science and Numerical Simulation},

volume = {56},

pages = {434-446},

abstract = {In this paper we present a new mutation procedure for Evolutionary Programming (EP) approaches, based on Iterated Function Systems (IFSs). The new mutation procedure proposed consists of considering a set of IFS which are able to generate fractal structures in a two-dimensional phase space, and use them to modify a current individual of the EP algorithm, instead of using random numbers from different probability density functions. We test this new proposal in a set of benchmark functions for continuous optimization problems. In this case, we compare the proposed mutation against classical Evolutionary Programming approaches, with mutations based on Gaussian, Cauchy and chaotic maps. We also include a discussion on the IFS-based mutation in a real application of Tuned Mass Dumper (TMD) location and optimization for vibration cancellation in buildings. In both practical cases, the proposed EP with the IFS-based mutation obtained extremely competitive results compared to alternative classical mutation operators.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CAMACHOGOMEZ201814,

title = {Active vibration control design using the Coral Reefs Optimization with Substrate Layer algorithm},

author = {C. Camacho-Gómez and X. Wang and E. Pereira and I. M. Díaz and Sancho Salcedo-Sanz},

url = {https://www.sciencedirect.com/science/article/pii/S0141029617311719},

doi = {https://doi.org/10.1016/j.engstruct.2017.12.002},

issn = {0141-0296},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Engineering Structures},

volume = {157},

pages = {14-26},

abstract = {Active vibration control (AVC) via inertial-mass actuators is a viable technique to mitigate human-induced vibrations in civil structures. A multi-input multi-output (MIMO) AVC has been previously proposed in the literature to simultaneously find the sensor/actuator pairs’ optimal placements and tune the control gains. However, the method involved local gradient-based methods, which is not affordable when the number of possible locations of actuators is large. In this case, the computation time to obtain a local solution may be huge and unaffordable, which limits the number of test points and/or actuators/sensors considered. This paper proposes an alternative approach based on a recently proposed meta-heuristic, the Coral Reefs Optimization (CRO) algorithm. More concretely, an enhanced version of the CRO is considered, the Coral Reefs Optimization with Substrate Layer (CRO-SL). The CRO-SL is a competitive co-evolution algorithm in which different exploration procedures are jointly evolved within a single population of potential solutions to the problem. The proposed algorithm is thus able to promote competition among different search methods to solve hard optimization problems. In terms of structural design, this work provides an important step to improve the applicability of AVC systems to real complex structures (with a large number of vibration modes and/or with a large number of test points) by achieving global optimum designs with affordable computation time. A finite element model of a real complex floor structure is used to illustrate the contributions of this paper.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SALCEDOSANZ201762,

title = {Structures vibration control via Tuned Mass Dampers using a co-evolution Coral Reefs Optimization algorithm},

author = {Sancho Salcedo-Sanz and C. Camacho-Gómez and A. Magdaleno and E. Pereira and A. Lorenzana},

url = {https://www.sciencedirect.com/science/article/pii/S0022460X17300391},

doi = {https://doi.org/10.1016/j.jsv.2017.01.019},

issn = {0022-460X},

year  = {2017},

date = {2017-01-01},

urldate = {2017-01-01},

journal = {Journal of Sound and Vibration},

volume = {393},

pages = {62-75},

abstract = {In this paper we tackle a problem of optimal design and location of Tuned Mass Dampers (TMDs) for structures subjected to earthquake ground motions, using a novel meta-heuristic algorithm. Specifically, the Coral Reefs Optimization (CRO) with Substrate Layer (CRO-SL) is proposed as a competitive co-evolution algorithm with different exploration procedures within a single population of solutions. The proposed approach is able to solve the TMD design and location problem, by exploiting the combination of different types of searching mechanisms. This promotes a powerful evolutionary-like algorithm for optimization problems, which is shown to be very effective in this particular problem of TMDs tuning. The proposed algorithm's performance has been evaluated and compared with several reference algorithms in two building models with two and four floors, respectively.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}