Rodriguez-Escoto, Joel-Novi
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Rodriguez-Escoto, Joel-Novi
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Rodríguez Escoto, Joel Novi
Alternative Name
jorodrigu
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ORCID
Scopus Author ID
57222721169
Researcher ID
DYI-5665-2022

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Book of abstracts CLAIO/CSMIO 2024 conference

2024 , Olivares-Benitez, Elias , Rodriguez-Escoto, Joel-Novi , M. Angélica Salazar-Aguilar , Paulina González-Ayala

El Book of Abstracts CLAIO/CSMIO 2024 es un compendio que incluye los resúmenes de las ponencias y estudios presentados en el XXII Congreso Latino Iberoamericano de Investigación Operativa (CLAIO) y el XII Congreso de la Sociedad Mexicana de Investigación de Operaciones (CSMIO). Este evento, celebrado del 28 de octubre al 1 de noviembre de 2024 en Guadalajara, México, reúne a investigadores y profesionales de Latinoamérica que trabajan en diversos campos de la Investigación Operativa. El libro contiene una amplia variedad de trabajos enfocados en temas de optimización matemática, simulación, inteligencia artificial, logística, programación estocástica, aprendizaje automático, transporte, gestión de la cadena de suministro, entre otros. Se presentan metodologías innovadoras, modelos y aplicaciones prácticas en diferentes áreas como la salud, el transporte y la sostenibilidad.

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A multi‐objective sustainable closed‐loop supply chain network problem with hybrid facilities

2024 , Rodriguez-Escoto, Joel-Novi , Olivares-Benitez, Elias , Nucamendi-Guillén, Samuel , Julie Drzymalski

AbstractA sustainable closed‐loop supply chain network requires conjunctive implementation of reverse logistics in the supply chain, with decisions that consider economic, environmental, and social factors. In real life, the problem needs to be addressed by prioritizing targets or interacting between them to give a range of solutions to the decision maker. In this context, this work proposes a novel multi‐objective sustainable closed‐loop supply chain network problem based on the revised network design model with hybrid recovery centers minimizing (1) the total economic cost, (2) the CO2 emission of vehicles used, and (3) the total obnoxious distance. The latter objective is a novel implementation of the social dimension of a sustainable model. A sensitivity analysis of the multi‐objective model is developed through ANOVA. A dataset of instances was generated to test the model and the solution methods, which are configured with AUGMECON2, a linear programming relaxation implemented to improve the CPU time, and AUGMECON2‐EXTENDED to obtain more solutions to avoid exploring all space of the solution. The results show that an AUGMECON2‐EXTENDED implementation outperforms all the selected performance metrics. These performance metrics include NPS, CPU time, RPOS, QM, and HV. The results show an improvement on average of at least , , , , and , respectively, in those metrics, in comparison to other implementations.

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Analysis of the Hiring Cost Impact with a Bi-objective Model for the Multi-depot Open Location Routing Problem

2021 , Rodriguez-Escoto, Joel-Novi , Nucamendi-Guillén, Samuel , Olivares-Benitez, Elias

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