Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Priority-aware collision avoidance via optimal velocity in multi-robot systems(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025) Sánchez Vaca, Luis Humberto; Sánchez Ante, Gildardo; mtyahinojosa, emipsanchez; Castañeda Cuevas, Herman; Hinojosa Cervantes, Salvador Miguel; Mercado Ravell, Diego Alberto; Escuela de Ingeniería y Ciencias; Campus Monterrey; Abaunza González, HernánThis thesis presents a decentralized control framework for prioritized multi-robot navigation that integrates Reciprocal Velocity Obstacles (RVO) with Bare-Bones Particle Swarm Optimization (BB-PSO). While velocity-based methods provide real-time geometric collision-avoidance guarantees, they often lead to oscillatory or conservative behaviors in dense environments and do not account for heterogeneous task priorities. On the other hand, optimization-based planners can shape agent behavior but lack inherent safety guarantees unless they are explicitly constrained. To address these limitations, the proposed framework combines two paradigms. First, RVO constructs a set of safe and admissible velocities. Then, BB-PSO selects the optimal velocity within this set based on a cost function that integrates priority-aware behaviors. This mechanism enables robots to navigate smoothly while respecting different task urgencies. Each robot independently computes its control command using local information about other agents, making this a fully decentralized operation. A simulation framework was developed to evaluate the proposed method across scenarios with different robot densities, priority distributions, and motion constraints. Experiments compare the hybrid controller against a greedy baseline using three metrics: arrival time, distance traveled, and collision occurrences. Results show that the hybrid approach improves navigation efficiency and significantly benefits high-priority agents by reducing their travel time and path deviation while maintaining safe interactions for the entire team. Overall, this thesis contributes a novel prioritized navigation strategy that combines geometric safety, real-time feasibility, and adaptive optimization. The approach represents a promising step toward scalable, priority-aware multi-robot systems that operate in complex and dynamic environments, with potential applications in automated warehouses, hospital logistics, and service robotics.
- View planning for three-dimensional environment reconstruction using the Next Best View method(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) Shain Ruvalcaba, Everardo; López Damian, Efraín; emipsanchez; Santana Díaz, Alfredo; López Damián, Efraín; School of Engineering and Sciences; Campus Ciudad de México; González Hernández, Hugo GustavoThis study was made with the purpose of understanding the impact of the objective functionand optimization methods on the Next Best View problem, which consists in finding the next position that the sensor or camera needs to take to scan an object or scenery in its totality. A simulated 5-Degree-of-Freedom mobile robot with a mounted simulated range sensor was used on a Virtual Reality Modeling Language environment, and the space discretization was made using a voxel map. For the objective function, two main factors were included: an area factor to make sure that the image taken by the sensor provides the best possible information, and a motion factor made up of distance and energy sub-factors to reduce the resources used by the robot, making multiple experiments on a laboratory scene to determine their best arrangement on the final objective function. Global optimization tasks such as a backstepping technique to escape local minima and a dynamic change in the objective function were implemented. The retrievement of the scene was made on an iterative process, with each iteration needing an optimization process for which three different methods were tested: Nelder-Mead, an Evolution Strategy, and Simulated Annealing. A set of experiments comparing the three methods in computational time and retrievement efficiency were made on three different environments with increasing difficulty to test their repeatability, with them being a laboratory model, a room with a cube and a pyramid inside it, and a study room with multiple furniture and windows.
- Optimization of kinetic and operating parameters in bioreactors using evolutionary algorithms(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-11) Barrera Hernández, Gonzalo Irving; Sosa Hernández, Víctor Adrián; emipsanchez; Alfaro Ponce, Mariel; Aranda Barradas, Juan Silvestre; Corrales Muñoz, David Camilo; School of Engineering and Sciences; Campus Estado de México; Gómez Acata, Rigel ValentínBioreactors play a role in creating biological products such as medicines and biofuels by care fully controlling factors such as substrate levels and temperature within them to obtain optimal production results, bioreactor production process poses a challenge that poses a challenge to engineers due to the intricate setup involved. In the field of microbiology and biotechnology, conventional approaches such as the Monod model, logistic growth models, and fed-batch techniques have been employed to predict and improve the growth conditions of microor ganisms and the production of proteins of interest in fermenters. However, these approaches could face challenges when they encounter nonlinear systems and conflicting objectives. To address these challenges, our suggestion is to approach the configuration of factors in bioreactors as an optimization problem using an evolutionary algorithm that can improve the effectiveness and quality of the operating process. The objective of this study is to in vestigate and create a pipeline that integrates evolutionary algorithms to solve multi-objective and scalar optimization problems, aimed at identifying kinetic and critical parameters within a bioreactor system. The optimization process involves, in the first stage, a least squares ap proach that considers product, biomass, dissolved oxygen, and substrate concentrations as objectives, with the kinetic parameters (e.g., maximum specific growth rate and substrate affinity) serving as decision variables. The second stage focuses solely on maximizing the amount of produced product, specifically biomass, using critical operational variables, such as feed rate and aeration, as decision variables. The research employs Escherichia coli as a microorganism that has been genetically al tered to produce orange fluorescent protein (OFP) to test the validity of improvement frame works. Initially, in the simulation and process tuning phase, experimental information, from batch cultures, is used to accurately determine the factors. Later, in the fed-batch phase, the application of an algorithm is used to optimize biomass yield while considering operational constraints such as oxygen levels and maximum reactor volume. The findings show that this method accurately calculates factors during the fed-batch phase and efficiently increases biomass production in the continuous fed phase. The use of algorithms such as multiple NSGA-III and single-objective genetic algorithms provides valuable benefits when dealing with intricate bioreactor configurations that have conflicting objectives such as managing substrate consumption and improving production yield. This approach has promising prospects for improving the accuracy and efficiency of bioprocess optimization, while increasing its scalability, in the field of biotechnology in the future.
- Charging EV station forecasting and location model for Mexico’s private sector(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-06-13) Hernández Salazar, Aldo; Ríos Solís, Yasmín Águeda; emimmayorquin; Jacobo Romero, Yulitza Yazmin; Shcool of Engineering and Sciences; Campus Monterrey; Probst, OliverThe decarbonization of the transport sector is critical for addressing climate change, with electric vehicles (EV) representing a pivotal solution. This thesis focuses on forecasting EV adoption and optimizing charging stations’ location in Mexico’s private sector. The study examines relevant national and international regulations and existing EV adoption models through a comprehensive literature review. Data collection incorporates national statistics, energy consumption records, and market reports on EV sales and adoption rates. Using statistical methods, the research develops multiple scenarios for EV adoption up to 2030. A mixed integer programming model is then constructed to maximize the profitability of charging station placements, considering constraints such as budget, parking availability, and electrical capacity. A detailed case study with anonymized data from Iberdrola’s clients is conducted, simulating the model to determine optimal charging station locations and configurations. The results provide valuable insights into the infrastructure needed to support the transition to EVs in Mexico, offering strategic recommendations for stakeholders. The study concludes with suggestions for future research, emphasizing the importance of real-time data and expanding the analysis to public charging infrastructure. This work aims to contribute significantly to Mexico’s sustainable energy transition and develop an efficient, widespread EV charging network.
- Advanced Optimization of the Mexican National Interconnected Transmission Grid: A Comprehensive Analysis of Power Losses, Greenhouse Gas Emissions, and Renewable Energy Curtailment(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-12-26) Vega Gómez, Oscar Alejandro; Flores Tlacuahuac, Antonio; emimmayorquin; Hernández Romero, Ilse María; Faculty of Engineering Sciences; Campus Monterrey; Probst Oleszewski, Oliver ProbstThis study presents a thorough investigation into the Mexican National Interconnected System’s (NIS) Transmission grid, employing a mathematical optimization model implemented in the Julia programming language. The principal focus is to optimize the dynamic behavior of the system, considering both renewable and conventional energy sources. The dispatch study spans from 2017 to 2022, with hourly annual generation resolution; it focuses on achieving optimal cost efficiency while simultaneously meeting the system’s de mand and analyzing the transmission power losses for different scenarios. The formulation systematically integrates factors such as bidirectional transmission flux, current flow, generation costs, greenhouse gas emissions including various pollutants, optimal operating policies, power losses, and transmission capacity. The study highlights the mismatch between generation and transmission capacity growth, providing detailed assessments of the impact of minimum generation levels and grid upgrades. The findings contribute valuable insights into addressing congestion issues, optimizing the grid, and promoting sustainable energy practices in the Mexican NIS. The study also addresses power flow and losses within the Mexican transmission grid, as well as the impacts of generating with higher generator minimum capacity levels. It covers environmental consequences, renewable energy curtailment, and congestion patterns arising from congestion and power losses.
- Tailoring metaheuristics for designing thermodynamic-optimal water based cooling devices for microelectronic thermal management applications(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06) Pérez Espinosa, Guillermo; TERASHIMA MARIN, HUGO; 65879; Terashima Marín, Hugo; emipsanchez; Ortiz Bayliss, José Carlos; Aviña Cervantes, Juan Gabriel; Escuela de Ingeniería y Ciencias; Campus Monterrey; Cruz Duarte, Jorge MarioHeat sinks provide a common and straightforward alternative to dealing with the Microelectronic Thermal Management (MTM) problem due to their simplicity of fabrication, low cost, and reliability of heat dissipation. The MTM problem is highly relevant in today's electronics industry, as new electronic devices' miniaturization and enhanced performance have increased their heat power generation. So, regarding the second law of thermodynamics, an optimal heat sink design can guarantee that the microelectronic components operate without jeopardizing their life span and performance. To solve this challenging problem, Metaheuristics~(MHs) have shown to be excellent alternatives due to their reliability, flexibility, and simplicity. Nevertheless, no single MH guarantees an overall outstanding performance. Thus, the motivation for this work is to open ample room for practitioners to find the proper solver to deal with a given problem without requiring extensive knowledge of heuristic-based optimization. This work studies the feasibility of implementing a strategy for Automatic Metaheuristic Design powered by a hyper-heuristic search to minimize the entropy generation rate of microchannel heat sinks and tailor population-based and metaphor-less MHs for solving the MTM. A mathematical model based on thermodynamic modeling via the Entropy Generation Minimization (EGM) criterion was used to obtain the value of the entropy generation rate of a rectangular microchannel heat sink according to their design. Four different scenarios were considered, varying the design specifications for the heat sinks and comparing our generated MH against seven well-known heuristic-based algorithms from the literature. The one-sided Wilcoxon signed ranked test was used to perform these comparisons. Statistical evidence was found to claim that our tailored MHs manage to outperform them, in most cases, at least in the tested scenarios. Additionally, we followed a methodology to infer which operators should be considered in a curated heuristic space to design the proper MH easily. We found that using this curated search space benefits the overall process, as the HH algorithm managed to tailor high-performing MHs faster and more consistently than its counterpart. Furthermore, insights were obtained on which HH parameters are more suitable for our search, as some can enhance the tailoring process when tuned correctly. Finally, we tested some of our best designs found to see how they perform when minor fluctuations appear on some variables, just as they occur in real-life implementations. All the experimentation processes also found that the search operators of evolutionary algorithms are well suited to solve this problem, as they compose several of our tailored MHs, and that the combination of High Thermal Conductive Graphite and water achieved the lower entropy generation rate values from the four combinations tested.
- An optimization approach for allocating cultural manifestations and spaces to increase cultural participation and improve social welfare in marginalized populations in Mexico(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-06-17) Arakanchi Weil, Eitan; ESPINOZA GARCIA, JUAN CARLOS; 251244; Espinoza García, Juan Carlos; puelquio/mscuervo; Murrieta Cortés, Beatriz; School of Engineering and Sciences; Campus Monterrey; Regis Hernández, FabiolaThe unequal distribution of cultural offers and infrastructure is a current problem in Mexico, where marginalized populations are the most disadvantaged. Alternatively, there is a severe social lag in many Mexican municipalities matching the unequal distributions of these resources. We analyze the interactions between social lag, population, cultural offer, cultural infrastructure, cultural budget, and cultural participation of the Mexican municipalities seeking to explain the social lag variability with a linear statistical model. Then, structural modeling using Interpretive Structural Modeling methodology was applied to explain the structural and dependence relationships between the factors seeking to explain cultural participation. The results from the structural modeling were used to define the structure of the factors in a dynamic model formulation, but more importantly, to define the criteria for a choice model formulation seeking to simulate the intention of locality populations to attend specific Spaces for Cultural Manifestations (SCM) or specific Cultural Manifestations (CM). Then, maximal covering and p-median location-allocation optimization models were proposed to maximize cultural participation and reduce the average distance to cultural manifestations in municipalities that contribute to the goals of the Official Newspapers of the Federation. These proposals consider both the preferences of people in localities, the compatibility between the SCM and CM, and budget and capacity constraints. Finally, the System Dynamic model was proposed to correctly explain social welfare and cultural participation variability given a failed approximation using a linear model. The model analysis could be very useful in the design and implementation of future public policies in the cultural sector and since previous studies have demonstrated the acute relationship between cultural consumption and social welfare, this research seeks to increase cultural participation in marginalized municipalities to generate more social welfare and quantify this phenomenon. Likewise, the motivation for this work is to properly manage the cultural resources in Mexico and other countries and positively influence the cultural and social public policies. The results first suggest that a linear statistical model is unable to explain social lag variability in terms of the proposed variables. Also, a structural proposal of the factors explaining cultural participation is made, being valuable information for the optimization and System Dynamics model. Then, applying a restriction guarantying specific minimum cultural participation in localities suggests that 13% minimum cultural participation leads to the best results in terms of the distribution of cultural resources, maximizing cultural participation and guarantying equity in cultural participation among localities. The scenario analysis in the maximal covering approach proposes that a distance-based scenario proposes a better distribution of resources but guaranties less cultural participation than the other scenarios. Alternatively, the scenario analysis with the p-median approach proposes that distance guided criterion generates the worst solutions of the model and increases the average distance to cultural manifestations. Finally, a dynamic model proposal of the cultural and social sector is made considers demographic aspects, cultural budget and infrastructure, and cultural participation and social welfare seeking to quantify the impact of the location-allocation proposal on the cultural participation and the impact of a cultural participation increase in the social welfare of municipalities. The results of this work lay the foundations for improving the cultural and social sector in Mexico, but more importantly, propose a generic model to be implemented in any territorial and political context.
- Impact of pulsed electric fields on fermentation process during yogurt production(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-06) Miranda Mejía, Graciela A.; MORALES DE LA PEÑA, MARIANA; 223211; Morales de la Peña, Mariana; puemcuervo; Arredondo Ochoa, Teresita; Gomez, Lorena; School of Engineering and Sciences; Campus Monterrey; Tejada Ortigoza, ViridianaA study on the effect of pulsed electric fields (PEF) application to the inoculum for natural drinkable yogurt production is presented in this dissertation. This research involves the fermentation time optimization of yogurt production through the application of PEF, as well as the evaluation of the proximal composition, physicochemical characterization, and a discriminatory sensory perception test immediately after processing and during storage of the obtained yogurt treated with PEF, having a control yogurt as a reference. Chapter 1 includes the motivation, problem statement, and context of this study. Chapter 2 is related to the hypothesis and objectives. Chapter 3 comprises the theoretical framework regarding yogurt production, Lacto-fermentation, and PEF principles and applications. Chapter 4 details the materials and methods to conduct the experimental work. Chapter 5 focuses on the results analysis and a discussion. Chapter 6 includes conclusions and recommendations. Finally, it is included a disclosure regarding scientific material and an appendix section containing complementary information collected during data organization and analysis. Overall, this master’s dissertation demonstrated that PEF technology is a potential alternative to optimize yogurt production processes through the reduction of fermentation time without significantly altering its proximal content and physicochemical characteristics and sensory perception, resulting in a final pro are included duct similar to that one obtained by the conventional process.
- Applications of artificial neural networks for experimental design optimization of Chlorella vulgaris microalgae growth(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022) Díaz Hernández, María Monserrat; CHAIREZ ORIA, JORGE ISAAC; 42787; dnbsrp; Parra Saldívar, Roberto; Escuela de Ingeniería y Ciencias; Campus Ciudad de México; Alfaro Ponce, MarielThis thesis proposes developing an optimization experimental model to optimize nutrient consumption and microalgae growth from the Novozymes company’s sidestream. The optimization model was created using the Box-Behnken experimental design for three factors. These three criteria were considered to raise the Chlorella v. biomass, and three different levels for each factor were chosen and implemented. The first factor chosen was CO2 since microalgae are important in producing energy for growth and proteins, lipids, and nucleoid acid. The second component chosen was agitation, which allows for the exchange of gases in the medium and the uniform consumption of nutrients from the medium. The day/night cycle was used to generate mixotrophic cultivation, which encouraged the culture to utilize the carbon in the sidestream while maintaining the green pigments of Chlorella vulgaris due to the presence of light. Following the experimentation phase, the best levels for each factor were 0.5% CO2, 70 RPM of agitation, and 8:16 hrs of day/night cycle. These amounts were used in a photobioreactor to cultivate and observe nutrient consumption behavior for eight days. Following these days, the COD level was reduced by 47.34%, the total nitrogen decrement was 48.70 %, the total phosphorus decrement was 96.42 %, and the dry biomass increased by 300 %. Simultaneously, a suitable neural network was designed to optimize the optimal levels for the same three parameters; this model was trained, validated, and evaluated using the experimental results. The ideal amounts for each factor were 0.5% CO2, 77 RPM of agitation, and 8:16 hours of day/night cycle. These levels were used in a photobioreactor to cultivate and observe nutrient consumption behavior for eight days. Following these days, the COD level declined by 40.80%, the total nitrogen decrement was 44.63%, the total phosphorus decrement was 98.65%, and the dry biomass increased by 400%. Both models are based on the work’s greatest contribution of reducing sidestream nutrients and promoting the increase in microalgae biomass in a shorter time than traditional methods that range from 12 to 14 days, as well as being a solution for treating wastewater from the enzyme manufacturing process.
- Location optimization of drug take-back boxes in the state of Pennsylvania(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-12-07) López Vázquez, Alejandro; López Soto, Diana; 366362; López Soto, Diana; puemcuervo, emipsanchez; Smith Cornejo, Neale Ricardo; School of Engineering and Sciences; Campus Monterrey; Griffin, PaulThe Opioid Use Disorder (OUD) crisis in the USA poses one of the greatest public health problems(Hodder et al., 2021), just in 2019 72.9% out of the 70,630 overdose deaths in the US were caused by opioids (CDC, 2021). One of the most important strategies to tackle OUD is the creation of community-based programs with only a few of them being objectively evaluated (Leece et al., 2019). PROSPER being is an evidence-based model which delivers scientifically proven, high-quality programs for communities has delivered several projects, one of them being the creation of new drug take-back boxes in collaboration with Penn State University Engineering students (R. Spoth & Greenberg, 2011; Wagner, 2020). The problem posed in this thesis is the need to locate a limited number of boxes in a way that the availability and coverage is maximized, taking into consideration that the box should be located in a secure and public place and in some cases considering other factors as Population rate, Dispensation rate, OD death rate, DUD rate, ED visit rate, number of boxes already in the county and the percentage to reach the goal, for which 4 optimization models were created. Two of the models had a county level scope then selecting the zip codes to be covered and the other two working directly with zip code, the other difference is that two of the models only focus on maximizing the population covered while the other two focus both in the population and all the other factor previously mentioned. The results rendered by the models place model 2 as the one that better increases the coverage of the population, both by the county average and total population, nevertheless model 4 has also a great coverage increase, but also considering all the additional factors that make it a mor relevant and adequate model for the purpose of combating the OUD crisis in the state of Pennsylvania.