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Lourdes Uribe - IEEE Xplore Author Profile

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Author details

Lourdes Uribe

Publications

3

Citations

4

Publications by Year

20242024

Co-Authors:

Carlos Artemio Coello CoelloLilla BekeEdmund K. BurkeJun ChenOziel Cortés-Piña

Show All Co-Authors (13)

Lourdes Uribe

Affiliation

Faculty of Actuarial Sciences of Universidad Anáhuac México, Mexico

Publication Topics

Air Control,
Constraint Handling,
Decoding,
Destination Node,
Dijkstra’s Algorithm,
Direct Representation,
Exact Algorithm,
Graph Layout,
Hybrid Genetic Algorithm,
Land Subsidence,
Local Search,
Localization Performance

Biography

Lourdes Uribe received the Ph.D. degree (cum laude) in physical-mathematical sciences from ESFM-Instituto Politécnico Nacional (IPN), Mexico City, Mexico, in 2020.,She is currently a Professor with the Mathematical Department of ESFM-IPN. Her major research interests are: hybrid algorithms, multiobjective optimization, and constraint-handling techniques.(Based on document published on 10 April 2023).

Publications

3

Citations

4

Publications by Year

20242024

Co-Authors:

Carlos Artemio Coello Coello
Lilla Beke
Edmund K. Burke
Jun Chen
Oziel Cortés-Piña

Show All Co-Authors (13)

Author's Published Works

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Showing 1-3 of 3 results

Early Access Articles (2)

Journals (1)

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Lourdes Uribe(3)
André Deutz(1)
Hao Wang(1)
Pablo Rosas(1)
Angel E. Rodriguez-Fernandez(1)
ESFM, Instituto Politécnico Nacional, Mexico City, Mexico(2)
School of Engineering and Materials Science, Queen Mary University of London, London, U.K(1)
Computer Science Department of the CINVESTAV, Mexico City, Mexico(1)
Faculty of Actuarial Sciences of Universidad Anáhuac México, Mexico(1)
applied quantum algorithms group Leiden University, The Netherland(1)
IEEE Transactions on Evolutionary Computation(3)
IEEE(3)
Media(2)
Air Control(1)
Constraint Handling(1)
Decoding(1)
Destination Node(1)
Dijkstra’s Algorithm(1)

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A Newton Method for Hausdorff Approximations of the Pareto Front Within Multi-objective Evolutionary Algorithms

Hao Wang;Angel E. Rodriguez-Fernandez;Lourdes Uribe;André Deutz;Oziel Cortés-Piña;Oliver Schütze

IEEE Transactions on Evolutionary Computation

Year: 2024 | Early Access Article |

A common goal in evolutionary multi-objective optimization is to find suitable finite-size approximations of the Pareto front of a given multi-objective optimization problem. While many multi-objective evolutionary algorithms have proven to be very efficient in finding good Pareto front approximations, they may need quite a few resources or may even fail to obtain optimal or nearly optimal approxi...Show More

A Newton Method for Hausdorff Approximations of the Pareto Front Within Multi-objective Evolutionary Algorithms

Hao Wang;Angel E. Rodriguez-Fernandez;Lourdes Uribe;André Deutz;Oziel Cortés-Piña;Oliver Schütze

IEEE Transactions on Evolutionary Computation

Year: 2024 | Early Access Article |

Riesz s-Energy as a Diversity Indicator in Evolutionary Multi-Objective Optimization

Jesús Guillermo Falcón-Cardona;Lourdes Uribe;Pablo Rosas

IEEE Transactions on Evolutionary Computation

Year: 2024 | Early Access Article |

Measuring the diversity of a Pareto Front Approximation (PFA) is critical when comparing the performance of Multi-Objective Evolutionary Algorithms (MOEAs). In the literature, some Quality Indicators (QIs) measure diversity according to their specific preferences. However, just a few QIs have mathematical properties proven. In this paper, we propose the Riesz s-energy (Es) as a QI to evaluate the ...Show More

Riesz s-Energy as a Diversity Indicator in Evolutionary Multi-Objective Optimization

Jesús Guillermo Falcón-Cardona;Lourdes Uribe;Pablo Rosas

IEEE Transactions on Evolutionary Computation

Year: 2024 | Early Access Article |

Routing and Scheduling in Multigraphs With Time Constraints—A Memetic Approach for Airport Ground Movement

Lilla Beke;Lourdes Uribe;Adriana Lara;Carlos Artemio Coello Coello;Michal Weiszer;Edmund K. Burke;Jun Chen

IEEE Transactions on Evolutionary Computation

Year: 2024 | Volume: 28, Issue: 2 | Journal Article |

Cited by: Papers (4)

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Routing and scheduling problems with increasingly realistic modeling approaches often entail the consideration of multiple objectives, time constraints, and modeling the system as a multigraph. This detailed modeling approach has increased computational complexity and may also lead to violation of the additivity property of the costs. In the worst scenario, increased complexity makes the problem i...Show More

Routing and Scheduling in Multigraphs With Time Constraints—A Memetic Approach for Airport Ground Movement

Lilla Beke;Lourdes Uribe;Adriana Lara;Carlos Artemio Coello Coello;Michal Weiszer;Edmund K. Burke;Jun Chen

IEEE Transactions on Evolutionary Computation

Year: 2024 | Volume: 28, Issue: 2 | Journal Article |

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