Marcela Quiroz

Marcela Quiroz
Universidad Veracruzana | UV · Centro de Investigación en Inteligencia Artificial

PhD

About

36
Publications
24,015
Reads
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269
Citations
Citations since 2016
20 Research Items
230 Citations
2016201720182019202020212022010203040506070
2016201720182019202020212022010203040506070
2016201720182019202020212022010203040506070
2016201720182019202020212022010203040506070
Introduction
Research interests: Experimental Algorithmics, Metaheuristics, Genetic Algorithms, Bin Packing, Machine Learning and Causal Inference Application areas: Logistics and Distributed Systems
Additional affiliations
August 2010 - present
Instituto Tecnológico de Ciudad Madero, (ITCM)
Position
  • Researcher

Publications

Publications (36)
Chapter
The Bin Packing Problem (BPP) is a classic optimization problem that is known for its applicability and complexity, which belongs to a particular class of problems called NP-hard, in which, given a set of items of variable size, we search to accommodate them inside fixed size containers, seeking to optimize the number of containers to be used, that...
Chapter
The study of causality has its origins more than 300 years ago; several disciplines have focused efforts on explaining the natural causal process, for example, Cognitive Psychology (CP) and Artificial Intelligence (AI). Performing a causal inference may be a simple task for humans, for that there are multiple efforts to replicate and explain causal...
Article
Full-text available
Solving scientific and engineering problems from the real world is a very complicated task, currently; hence, the development of powerful search and optimization techniques is of great importance [...]
Article
Full-text available
Several real optimization problems are very difficult, and their optimal solutions cannot be found with a traditional method. Moreover, for some of these problems, the large number of decision variables is a major contributing factor to their complexity; they are known as Large-Scale Optimization Problems, and various strategies have been proposed...
Article
Full-text available
This work presents a proposal for the automated parameter tuning problem (APTP) modeled as a bilevel optimization problem. Different definitions and theoretical results are given in order to formalize the APTP in the context of this hierarchical optimization problem. The obtained bilevel optimization problem is solved via a population-based algorit...
Book
Solving scientific and engineering problems from the real world is currently a very complicated task; that is why the development of powerful search and optimization techniques is of great importance. Two well-established fields focus on this duty; they are (i) traditional numerical optimization techniques and (ii) bio-inspired metaheuristic method...
Chapter
Full-text available
The one-dimensional Bin Packing Problem (BPP) is one of the best-known optimization problems, and it has a significant number of applications. For this reason, several strategies have been proposed to solve it, but only few works have focused on the study of the characteristics that distinguish the BPP instances and that could affect the performanc...
Article
Grouping problems are combinatorial optimization problems, most of them NP-hard, related to the partition of a set of items into different groups or clusters. Given their numerous real-world applications, different solution approaches have been presented to deal with the high complexity of NP-hard grouping problems. However, the Grouping Genetic Al...
Chapter
Full-text available
Parallel-machine scheduling problems are well-known NP-hard combinatorial optimization problems with many real-world applications. Given the increasing appearance of these problems, over the last few years, several algorithms have been developed to solve them, and different instances of these problems have been designed to be used as the benchmark...
Preprint
Full-text available
Grouping problems are combinatorial optimization problems, most of them NP-hard, related to the partition of a set of items into different groups or clusters. Given their numerous real-world applications, different solution approaches have been presented to deal with the high complexity of NP-hard grouping problems. However, the Grouping Genetic Al...
Preprint
Full-text available
This paper studies the physical layer security (PLS) of a vehicular network employing reconfigurable intelligent surfaces (RISs). RIS technologies are emerging as an important paradigm for the realisation of next-generation smart radio environments, where large numbers of small, low-cost and passive elements, reflect the incident signal with an adj...
Article
Full-text available
Grouping problems are a special type of combinatorial optimization problems that have gained great relevance because of their numerous real-world applications. The solution process required by some grouping problems represents a high complexity, and currently, there is no algorithm to find the optimal solution efficiently in the worst case. Consequ...
Chapter
User Interface Design Patterns (UIDPs) improve the interaction between users and e-applications through the use of interfaces with a suitable and intuitive navigability without restrictions on the size of the screen to show the content. Nowadays, UIDPs are frequently used in the development of new mobile apps. In fact, mobile apps are ubiquitous: i...
Chapter
This work introduces an agent-based model for the analysis of macroeconomic signals. The Bottom-up Adaptive Model (BAM) deploys a closed Walrasian economy where three types of agents (households, firms and banks) interact in three markets (goods, labor and credit) producing some signals of interest, e.g., unemployment rate, GDP, inflation, wealth d...
Conference Paper
Full-text available
Recently, Internet of Things (IoT) have witnessed significant attention due to their potential of bringing massive number of interconnected heterogeneous sensor nodes to collect big data for harnessing knowledge thus enabling real time monitoring and control. These wireless sensors relay their packets on to the base station via multi-hop transmissi...
Conference Paper
Full-text available
Internet of things (IoT) is considered to revolutionize the way internet works and bring together the concepts such as machine to machine (M2M) communication, big data, artificial intelligence, etc. to work under a same umbrella such that cyber space and human (physical systems) are more intertwined and thus ubiquitous giving rise to cyber physical...
Chapter
A good management of operating rooms is an important concern for hospitals. Being aware of that fact, the public hospital “Hospital General de Cd. Juárez” has specially announced it as a priority objective to reach. After analyzing the scheduling process at that hospital, we proposed to the hospital Administration to apply a genetic algorithm to sc...
Chapter
Full-text available
This chapter presents a novel hybrid algorithm for the quay crane scheduling problem (QCSP). QCSP consists of scheduling a sequence of unloading and loading movements for cranes assigned to a vessel, minimizing the total completion time of all the tasks. The proposed algorithm integrates two well-known metaheuristics: Greedy Randomized Adaptive Sea...
Article
Full-text available
In this study, the one-dimensional Bin Packing Problem (BPP) is approached. The BPP is a classical optimization problem that is known for its applicability and complexity. We propose a method that is referred to as the Grouping Genetic Algorithm with Controlled Gene Transmission (GGA-CGT) for Bin Packing. The proposed algorithm promotes the transmi...
Thesis
Full-text available
Throughout the search for the best possible solutions for NP-hard problems, a wide variety of heuristic algorithms have been proposed, however, despite the efforts of the scientific community to develop new strategies, there is no efficient algorithm capable of finding the best solution for all possible situations. Recent works in experimental anal...
Chapter
Full-text available
Recent works in experimental analysis of algorithms have identified the need to explain the observed performance. To understand the behavior of an algorithm it is necessary to characterize and study the factors that affect it. This work provides a summary of the main works related to the characterization of heuristic algorithms, by comparing the wo...
Chapter
Full-text available
This paper promotes the application of empirical techniques of analysis within computer science in order to construct models that explain the performance of heuristic algorithms for NP-hard problems. We show the application of an experimental approach that combines exploratory data analysis and causal inference with the goal of explaining the algor...
Chapter
Full-text available
The performance of the algorithms is determined by two elements: efficiency and effectiveness. In order to improve these elements, statistical information and visualization are key features to analyze and understand the significant factors that affect the algorithm performance. However, the development of automated tools for this purpose is difficu...
Article
This article addresses a classical problem known for its applicability and complexity: the Bin Packing Problem (BPP). A hybrid grouping genetic algorithm called HGGA-BP is proposed to solve BPP. The proposed algorithm is inspired by the Falkenauer grouping encoding scheme, which applies evolutionary operators at the bin level. HGGA-BP includes effi...
Chapter
Full-text available
This chapter approaches the Truck Loading Problem, which is formulated as a rich problem with the classic one dimensional Bin Packing Problem (BPP) and five variants. The literature review reveals that related work deals with three variants at the most. Besides, few efforts have been done to combine the Bin Packing Problem with the Vehicle Routing...
Article
Full-text available
Resumen. En este artículo se aborda un problema clásico muy conocido por su aplicabilidad y complejidad: el empacado de objetos en contenedores (Bin Packing Problem, BPP). Para la solución de BPP se propone un algoritmo genético híbrido de agrupación denominado HGGA-BP. El algoritmo propuesto está inspirado en el esquema de representación de grupos...
Chapter
The algorithms are the most common form of problem solving in many science fields. Algorithms include parameters that need to be tuned with the objective of optimizing its processes. This work uses Hoeffding race techniques, with the objective to obtain the best initial combination of variables to use it as an input configuration. Hoeffding race qu...
Conference Paper
Causal inference can be used to construct models that explain the performance of heuristic algorithms for NP-hard problems. In this paper, we show the application of causal inference to the algorithmic optimization process through an experimental analysis to assess the impact of the parameters that control the behavior of a heuristic algorithm. As...
Conference Paper
Some Hybrid Packing Systems integrate several algorithms to solve the bin packing problem (BPP) based on their past performance and the problem characterization. These systems relate BPP characteristics with the performance of the set of solution algorithms and allow us to estimate which algorithm is to yield the best performance for a previously u...
Thesis
Full-text available
La mayoría de los problemas de optimización del mundo real pertenecen a una clase especial de problemas denominada NP-duro, lo cual implica que no se conocen algoritmos eficientes para encontrar la solución óptima en el peor caso. Para la solución de este tipo de problemas, el esfuerzo de muchos investigadores ha concretado en una variedad de algor...

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Projects

Projects (2)
Project
Building robust and highly effective heuristics that incorporate knowledge of the problem-domain to solve the NP-hard grouping problem Parallel-machine scheduling R||Cmax.