Martínez Ríos, Félix Orlando
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Martínez Ríos, Félix Orlando
Official Name
Martínez Ríos, Félix Orlando
Alternative Name
fmartin
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ORCID
Scopus Author ID
24339038500
Researcher ID
N-7502-2018

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New Particle Swarm Optimizer Algorithm with Chaotic Maps for Combinatorial Global Optimization Problems. An Application to the Deconvolution of Mössbauer Spectra

2024-01-01 , Martínez Ríos, Félix Orlando , Jiménez-López, Omar , Alvarez Guillen, Luis Alejandro

In this chapter, we present a novel method for addressing global optimization problems inspired by evolutionary algorithms found in nature. We integrate the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithm with random value generation based on chaotic maps. The resulting algorithm is applied to the computationally complex task of deconvoluting Mossbauer spectra. We implement ten chaotic maps to generate random values and compare their performance with traditional random number generators. Through experiments, we demonstrate that the developed algorithm excels in exploring the search space and exhibits fast intensification in finding the global minimum. In addition, we perform a comprehensive review of existing solutions to the Mossbauer spectrum deconvolution problem, highlighting the scarce availability of developments in this area. We also present a user-friendly program designed with an intuitive interface to facilitate the deconvolution process by Spector Mossbauer. This program will be freely distributed without operational restrictions. Experimental validation is performed on Mossbauer spectra generated using the developed program and those obtained by experimental means, affirming the efficiency of the new algorithm conceived. ©Springer.

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An Alternative Method for the Optimum Dynamic Balancing of the Four-Bar Mechanism

2014 , Acevedo, Mario , Haro-Sandoval, Eduardo , Martínez Ríos, Félix Orlando

This article presents the optimum dynamic balancing of the four-bar mechanism, in particular the crank-rocker, by the addition of counterweights. This is done by imposing as little restrictive as possible constraints on the counterweights parameters. First the general analytical equations of motion of the crank-rocker four-bar mechanism are obtained, using natural coordinates. This model allows expressing the dynamic equations of the mechanism just in terms of the mass, as opposed to the need of using also the moment of inertia, and the coordinates of the center of gravity of the counterweights, that are used as optimization variables. This implies that no particular counterweight shape is assumed in advance. The only constraints imposed on these optimization variables are that masses must be non-negative. As a novelty, the most influencing variables in the optimization are identified using a global sensitivity analysis based on polynomial chaos. This allows to impose different constraints an also to reduce the total number of optimization variables without affecting the global results. The results obtained are validated by simulations, and compared to those expressed in representative papers obtained by other authors. © Springer Nature

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