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Jaime Mora-Vargas

Researcher at Monterrey Institute of Technology and Higher Education

Publications -  37
Citations -  186

Jaime Mora-Vargas is an academic researcher from Monterrey Institute of Technology and Higher Education. The author has contributed to research in topics: Population & Computer science. The author has an hindex of 7, co-authored 29 publications receiving 155 citations.

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Journal ArticleDOI

A Comprehensive Framework for the Analysis of Industry 4.0 Value Domains

TL;DR: In this paper, the authors explore the value creation process within Industry 4.0, with special emphasis on its relationship with mass customization and the sustainability issue, based on the identified research gaps and opportunities derived from a literature review of relevant concepts.
Journal ArticleDOI

The impact of carbon footprinting aggregation on realizing emission reduction targets

TL;DR: In this paper, the authors implement a detailed estimation method based on NTM and different aggregate approaches for transportation carbon emissions in the dynamic lot sizing model. But, the limitations of aggregate models for both accurate estimation of real emissions and risks of compliance with carbon constraints (e.g., carbon caps).
Journal Article

The impact of carbon footprinting aggregation on realizing emission reduction targets

TL;DR: In this article, the authors implement a detailed estimation method based on NTM and different aggregate approaches for transportation carbon emissions in the dynamic lot sizing model. But, the limitations of aggregate models for both accurate estimation of real emissions and risks of compliance with carbon constraints (e.g., carbon caps).
Book ChapterDOI

An Efficient Simulated Annealing Algorithm for Feasible Solutions of Course Timetabling

TL;DR: A new Simulating Annealing (SA) algorithm for CTP is presented that is able to find a feasible solution in instances where no other algorithm in the literature has been reported a success.
Journal ArticleDOI

A multi-criteria vertical coordination framework for a reliable aid distribution

TL;DR: In this article, a methodology that translates multiple humanitarian supply chain stakeholders' preferences from qualitative to quantitative values, enabling these preferences to be integrated into optimization models to ensure their balanced and simultaneous implementation during the decision-making process is proposed.