Sergio Gerardo de-los-cobos-silva

Sergio Gerardo de-los-cobos-silva
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Sergio verified their affiliation via an institutional email.
  • Dr. in engineering. and Dr. in Economic and Admistrative Sciences
  • Professor C (Full) at Metropolitan Autonomous University

About

80
Publications
8,890
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215
Citations
Introduction
Skills and Expertise
Current institution
Metropolitan Autonomous University
Current position
  • Professor C (Full)
Additional affiliations
Metropolitan Autonomous University
Position
  • Professor (Full)

Publications

Publications (80)
Article
Full-text available
In this study, we introduce an innovative approach that utilizes complex networks and the k_core method to address community detection in weighted networks. Our proposed bi-objective model aims to simultaneously discover non-overlapping communities while ensuring that the degree of similarity remains below a critical threshold to prevent network de...
Article
Full-text available
In this study, we propose a novel methodology called Particle Dynamics Method (PDM) for identifying and quantifying influential nodes in complex networks. Inspired by Newton’s three laws of motion and the universal gravitation law, PDM is based on a mathematical programming method that leverages node degrees and shortest path lengths. Unlike tradit...
Article
Nowadays, biometric authentication has gained relevance due to the technological advances that have allowed its inclusion in many daily-use devices. However, this same advantage has also brought dangers, as spoofing attacks are now more common. This work addresses the vulnerabilities of automatic speaker verification authentication systems, which a...
Article
Full-text available
The detection of communities in complex networks offers important information about the structure of the network as well as its dynamics. However, it is not an easy problem to solve. This work presents a methodology based of the robust coloring problem (RCP) and the vertex cover problem (VCP) to find communities in multiplex networks. For this, we...
Preprint
Full-text available
In this work we present a methodology based on the robust coloring problem (RCP) and the vertex cover problem (VCP) in order to find the communities in multiplex networks. For this, we consider that the RCP finds a partial detection based on the similarity of connected and unconnected nodes and using VCP we look for that number of groups (previousl...
Article
Full-text available
This work analyzes and characterizes the spread of the COVID-19 disease in Mexico, using complex networks and optimization approaches. Specifically, we present two methodologies based on the principle of the rupture for the GC and Newton's law of motion to quantify the robustness and identify the Mexican municipalities whose population causes a fas...
Article
Full-text available
In this work, we propose a methodology to quantify robustness in networks. Specifically, the methodology is based on the resolution of the Vertex Separator Problem in order to find the set of nodes that the elimination of their links causes the rupture of the giant component. The methodology presented in this work was tested on a set of benchmark n...
Article
Full-text available
In this work, we present two matheuristic techniques based on two heuristic techniques: Ant system (AS), method of musical composition (MMC) and two exact methods: Primal-dual algorithm (PDA) and dual simplex algorithm (DSA). These techniques are denoted as DS-AS-PDA and DS-MMC-AS and are characterized by taking advantage of the information of the...
Article
Full-text available
Sex classification is a challenging open problem in computer vision. It is useful from statistics up to people recognition on surveillance video. So far, the best performance can be achieved by using 3D cameras, but this approach requires the use of some especial hardware. Other 2D approaches achieve good results on normal situations but fail when...
Article
Full-text available
Inverse percolation is known as the problem of finding the minimum set of nodes whose elimination of their links causes the rupture of the network. Inverse percolation has been widely used in various studies of single-layer networks. However, the use and generalization of multiplex networks have been little considered. In this work, we propose a me...
Article
Full-text available
In this work, we present a methodology to identify COVID-19 spreaders using the analysis of the relationship between socio-cultural and economic characteristics with the number of infections and deaths caused by the COVID-19 virus in different countries. For this, we analyze the information of each country using the complex networks approach, speci...
Article
Full-text available
EEn este trabajo, se presentan dos técnicas matheurísticas basadas en dos técnicas heurísticas: Sistema de hormigas (AS), método de composición musical (MMC) y dos métodos exactos: Algoritmo primal-dual (PDA) y algoritmo simplex dual (DSA). Estas técnicas se denotan como DS-ASPDA y DS-MMC-AS y se caracterizan por aprovechar la información de la est...
Chapter
The evaluation of individual universities generates university rankings according to a set of indicators. In general, the classical rankings are based on reputation, academic achievements, research levels, material and financial resources, etc. In this chapter, a new methodology for university rankings based on the maximum clique problem in network...
Article
Full-text available
Redistricting is the process of partitioning a set of basic units into a given number of larger groups for electoral purposes. These groups must follow federal and state requirements to enhance fairness and minimize the impact of manipulating boundaries for political gain. In redistricting tasks, one of the most important criteria is equal populati...
Article
Full-text available
El artículo describe un nuevo método para resolver laberintos cuadrados usando una versión aleatorizada de búsqueda a profundidad. El algoritmo propuesto se probó en dos familias de laberintos, una de ellas basada en el método de Aldous-Broder y el otro en el de Backtrack. El algoritmo de solución se compara con el método de Dijkstra, que es una té...
Article
Full-text available
El objetivo de este trabajo es evaluar la eficacia de una política ambiental que promueva la sustitución de energías fósiles por renovables, con la finalidad de reducir gradualmente las emisiones de dióxido de carbono a lo largo de un periodo. Se utiliza un modelo dinámico de equilibrio general computable para la economía mexicana y se simulan esce...
Article
To facilitate the redistricting process in Mexico, the authors designed two optimization algorithms; one is based on simulated annealing, and the other is based on artificial bee colony. In this paper, they describe their methodology and the results they obtained when they used these algorithms.
Article
This work focuses predominantly on unconstrained optimization problems and presents an original algorithm (the code can be downloaded from Ref. 1), which is used for solving a variety of benchmark problems whose dimensions range from 2 to 2.5 millions, using only 3 particles. The algorithm was tested in 36 benchmark continuous unconstrained optimiz...
Article
Full-text available
Many real-world problems can be seen as constrained nonlinear optimization problems (CNOP). These problems are relevant because they frequently appear in many industry and science fields, promoting, in the last decades, the design and development of many algorithms for solving CNOP. In this paper, seven hybrids techniques, based on particle swarm o...
Conference Paper
Nonlinear regression is a statistical technique widely used in research which creates models that conceptualize the relation among many variables that are related in complex forms. These models are widely used in different areas such as economics, biology, finance, engineering, etc. These models are subsequently used for different processes, such a...
Conference Paper
The constrained portfolio optimization problem with multi-objective functions cannot be efficiently solved using exact techniques. Thus, heuristics approaches seem to be the best option to find high quality solutions in a limited amount of time. For solving this problem, this paper proposes an algorithm based on the Method of Musical Composition (M...
Chapter
Redistricting is the redrawing of the boundaries of legislative districts for electoral purposes in such a way that Federal or state requirements are fulfilled. In 2015 the National Electoral Institute of Mexico carried out the redistricting process of 15 states using a nonlinear programming model where population equality and compactness were cons...
Conference Paper
The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes, in such a way that federal or state requirements are fulfilled. In Mexico, both population equality and compactness of the designed districts are considered as two conflicting objective functions. The present work represents the f...
Article
Full-text available
Los clasificadores no supervisados permiten un método de agrupación de forma automatizada. Para ello es deseable agrupar los elementos con un menor procesamiento de datos. Este trabajo propone un sistema clasificador no supervisado que utiliza el modelo de coloración de gráficassuaves. El método se puso a prueba con algunas instancias clásicas de l...
Article
Purpose This paper aims to propose comparing the performance of three algorithms based on different population-based heuristics, particle swarm optimization (PSO), artificial bee colony (ABC) and method of musical composition (DMMC), for the districting problem. Design/methodology/approach In order to compare the performance of the proposed algori...
Article
Redistricting is the redrawing of the boundaries of legislative districts for electoral purposes in such a way that the generated districts fulfill federal and state requirements such as contiguity, population equality and compactness. Redistricting is a multi-objective problem which has been proved to be NP-hard. In Mexico, the redistricting proce...
Article
Full-text available
In this paper a novel fuzzy convergence system (SC) and its fundamentals are presented. The model was implemented on a monoobjetive PSO algorithm with three phases: 1) Stabilization, 2) generation and breadthfirst search, and 3) generation and depth-first. The system SC-PSO-3P was tested with several benchmark engineering problems and with several...
Article
In this paper a Soft Graph Coloring Model is proposed, which is colored based on weights on the edges of the graph. It is shown that this model is very flexible and includes other similar problems such as Minimal, Equitable, Weak, and Robust Graph Coloring. A linear binary solution model and some test instances are also proposed.
Article
In this paper a novel system of convergence (SC) is presented as well as its fundamentals and computing experience. An implementation using a novel mono-objetive particle swarm optimization (PSO) algorithm with three phases (PSO-3P): stabilization, generation with broad-ranging exploration and generation with in-depth exploration, is presented and...
Conference Paper
Full-text available
Districting is the redrawing of the boundaries of legislative districts for electoral purposes in such a way that the Federal or state requirements, such as contiguity, population equality, and compactness, are fulfilled. The resulting optimization problem involves the former requirement as a hard constraint while the other two are considered as co...
Article
Full-text available
This paper presents an original and efficient PSO algorithm, which is divided into three phases: (1) stabilization, (2) breadth-first search, and (3) depth-first search. The proposed algorithm, called PSO-3P, was tested with 47 benchmark continuous unconstrained optimization problems, on a total of 82 instances. The numerical results show that the...
Article
Full-text available
In this paper a novel system of convergence (SC) is presented as well as its fundamentals and computing experience. An implementation using a novel mono-objetive particle swarm optimization (PSO) algorithm with three phases (PSO-3P): stabilization, generation with broad-ranging exploration and generation with in-depth exploration, is presented and...
Article
Full-text available
In this paper a Soft Graph Coloring Model is proposed, which is colored based on weights on the edges of the graph. It is shown that this model is very flexible and includes other similar problems such as Minimal, Equitable, Weak, and Robust Graph Coloring. A linear binary solution model and some test instances are also proposed.
Chapter
Nonlinear regression is a statistical technique widely used in research which creates models that conceptualize the relation among many variables that are related in complex forms. These models are widely used in different areas such as economics, biology, finance, engineering, etc. These models are subsequently used for different processes, such a...
Chapter
Since 2004, the Federal districting processes have been carried out using a Simulated Annealing based algorithm. However, in 2014, for the local districting of the state of México, a traditional Simulated Annealing technique and an Artificial Bee Colony based algorithm were proposed. Both algorithms used a weight aggregation function to manage the...
Article
Full-text available
Este trabajo presenta la comparación de los resultados de las técnicas heurísticas de ABC colonias de abejas artificiales (Artificial Bee Colony) y PSO enjambres de partículas (Particle Swarm Optimization) que son utilizadas para la estimación de parámetros de modelos de regresión no lineal. Los algoritmos fueron probados sobre 27 bases de datos de...
Article
This paper shows the comparison results of ABC (Artificial Bee Colony) and PSO (Particle Swarm Optimization) heuristic techniques that were used to estimate parameters for nonlinear regression models. The algorithms were tested on 27 data bases from the NIST collection (2001), 8 of these are considered to have high difficulty, 11 medium difficulty...
Article
Full-text available
En este trabajo se introduce tanto a la Programación Posibilística como a la Programación Borrosa como paradigmas que permiten resolver problemas de optimización cuando los coeficientes del modelo de programación lineal o las restricciones del mismo se presentan como números borrosos, en lugar de números exactos (crisp, en inglés). Se presentan alg...
Article
This work introduce to the Possibilistic Programming and the Fuzzy Programming as paradigms that allow to resolve problems of linear programming when the coefficients of the model or the restrictions on the same are presented as fuzzy numbers, rather than exact numbers (crisp). This work presents some examples based on [1].
Article
Full-text available
Redistricting is the redrawing of the boundaries of legislative districts for electoral purposes in such a way that the generated districts fulfill federal and state requirements such as contiguity, population equality and compactness. In this paper we solve the problem by means of a single objective and a multiobjective simulated annealing algorit...
Article
Full-text available
Este trabajo presenta los resultados de la tecnica heuristica de ABC (Artificial Bee Colony) utilizada para estimar los parametros de modelos de regresion no lineal. El algoritmo fue probado sobre 27 bases de datos de la coleccion NIST (2001), de las cuales 8 se consideran con un alto grado de dificultad. Se presentan los resultados experimentales.
Article
The practice of applying curve fitting techniques to describe data is widespread in many fields: in biology, in medicine, in engineer, in economy, etc. This paper presents a heuristic technique named Particle Swarm Optimization to be used for parameter estimation in regression models. The algorithm was tested on 27 databases for nonlinear models an...
Article
This article shows the results of ABC heuristic techniques (Artificial Bee Colony) that were used to estimate parameters for nonlinear regression models. The algorithm was tested on 27 data bases from the NIST collection (2001), 8 of these are considered to be high difficulty. Experimental results are presented.
Article
In this paper, the performance of two classical algorithms (simulated annealing and a discrete artificial bee colony) are compared on the redistricting problem, using a real example in Mexico and highlighting the superiority of the latter.
Article
Full-text available
The design of compact zones has been studied because of its influence in the creation of zones with regular forms, which are easier to analyze, to investigate or to administer. This paper propose a new method to measure compactness,by means of the transformation of the original geographical spaces, into figures formed with square cells, which are u...
Article
The design of compact zones has been studied because of its influence in the creation of zones with regular forms, which are easier to analyze, to investigate or to administer. This paper propose a new method to measure compactness,by means of the transformation of the original geographical spaces, into figures formed with square cells, which are u...
Article
Full-text available
Resumen En todos los tiempos uno de los temas de mayor interés a todos los niveles de la actividad humana es el referente a las percepciones salariales que se tienen. Incluso se podría decir que la decisión de seguir ciertos estudios ha dependido en gran manera sobre las perspectivas que el individuo tiene sobre el futuro de sus ingresos, por lo qu...
Article
Full-text available
The objective of this paper is to disseminate the technique of fuzzy regression and to give a practical example of its use. To this end, classical regression is compared to several fuzzy regression models on a problem concerning the consumer confidence index with respect to the dollar rate, the latter taken as the independent variable. A brief intr...
Article
The objective of this paper is to disseminate the technique of fuzzy regression and to give a practical example of its use. To this end, classical regression is compared to several fuzzy regression models on a problem concerning the consumer confidence index with respect to the dollar rate, the latter taken as the independent variable. A brief intr...
Article
Full-text available
The joint replenishment problem (JRP) has been studied for over 30 years and there are both heuristic and exact algorithms to determine the frequency of orders and fundamental cycle; in recent years it has been considered the model with stochastic demand. If we assume a behavior of normal distribution for the demand, we may obtain a non linear mixe...
Article
Full-text available
This work introduced to the problem of routering and optimum design of networks of computers that must satisfy certain practical conditions of interconnectivity. This paper show an approach style Steiner problems, and search robust and more economic solutions.
Article
Full-text available
The Robust Coloring Problem (RCP) is a NP-Hard Problem for which fast and efficient heuristic algorithms has been developed. In this work we present as a PCR the problem of assignment of frequencies for a cellphone grid. Some instances for this model are proposed and solved using a GRASP algorithm. Evidence shows that the intermittent interruptions...
Article
Compactness is an important principle in redistricting process, and there are different measures to quantify this property in electoral zones. However, these measures are unsatisfactory, since they can be unable to favor the design of compact zones in enough complicated problems. In this paper, we propose that a compactness measure may be unable to...
Article
In this paper the well-known p-median problem is tackled using a version of a heuristic bee algorithm. The proposed bee algorithm is explained and applied to eight different data sets. The results obtained are then compared to a classical, but effective, heuristic algorithm called the vertex substitution heuristic. The results on these data sets sh...
Article
Full-text available
In this paper an introduction is given to a multiple-item inventory problem, known as the Joint Replenishment Problem (JRP). This is a real world problem which has been extensively studied. The JRP has a continuous decision variable, and as many discrete decision variables as products that are ordered and produced. An exact method, given by Goyal,...
Article
Full-text available
In this paper an heuristic algorithm is developed. Its implementation is developed as well, in order to solve a sampling problem in the urban transportation network in Mexico City. The problem consist of the selection of at least 2 points (stops) on each of the 236 routes in the study comprising a total of 8390 stops. This problem is presented as a...
Article
Full-text available
En este artículo se desarrolla un algoritmo heurístico y su correspondiente implementación para resolver un problema de localización de plantas (facility location) de gran escala, en donde surgen potencialmente más de 640 plantas a localizar a lo largo de la República Mexicana. Originalmente se trató de obtener solución exacta al problema, usando d...
Article
Full-text available
The aim of the present paper is twofold. Firstly an introduction to the ideas of Support Vector regression is given. then a new and simple algorithm, suggested by the work of Campbell y Cristianini in [16], is proposed which solves the corresponding quadratic programming problem in an easy fashion. The algorithm is illustrated by example and compar...
Conference Paper
The purpose of the present paper is to compare the performance of scatter search (SS) against one of the best heuristics, known as the RAND algorithm (Kaspi and Rosenblatt [7]), in order to solve a popular and useful multi-product inventory problem referred to in the literature as the joint replenishment problem (JRP). The JRP is a classical proble...
Article
Full-text available
We implement the combinatorial optimization technique known as tabu search in the parameter estimation problem in a given non linear model. For the generation of neighbors, the implementation is based on a discretization of the parameter space, which is covered by a mesh. We present some comparative results on real or simulated data.
Article
Relevant Component Analysis has been introduced recently as a way to incorporate a priori information, such as class or preference information, that may exist for a given data set. The method uses this information to define a new Mahalanobis distance metric on the data space. The purpose of the present paper is to investigate the difference, if any...
Article
Full-text available
Many data analysis problems deal with non supervised partitioning of a data set, in non empty clusters well separated between them and homogeneous within the clusters. An ideal partitioning is obtained when any object can be assigned a class without ambiguity. The present paper has two main parts; first, we present different methods and heuristics...
Article
A formula that calculates the number of n x m matrices in A(R, S) was presented by Wang (Sci. sinica Ser. A 1 (1988) 1). This formula has 2(n) - 2n variables. Later, in 1998, a reduced formula was proposed by Wang and Zhang, in which the number of involved variables was reduced to only 2(n-1) -n. The reduction in the number of variables is importan...
Article
Contenido: Conceptos básicos; Probabilidad condicional e independencia; Variables aleatorias; Esperanza matemática; Algunas funciones de distribución; Temas adicionales.

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