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Computing and Systemic Tools to Address Engineering and Sustainable Challenges

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 2465

Special Issue Editors


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Guest Editor
Academic Area of Engineering and Architecture, Autonomous University of Hidalgo, Pachuca 42060, Mexico
Interests: cellular automata; evolutionary algorithms; metaheuristics; emergent optimization techniques

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Guest Editor
Academic Area of Engineering and Architecture, Autonomous University of Hidalgo, Pachuca 42060, Mexico
Interests: sustainable urban systems; low-impact technologies; urban hydrology; hydrogeochemistry

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Guest Editor
Academic Area of Engineering and Architecture, Autonomous University of Hidalgo, Pachuca 42060, Mexico
Interests: active databases; Petri nets; programming languages; simulation; artificial intelligence

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Guest Editor
Academic Area of Engineering and Architecture, Autonomous University of Hidalgo, Pachuca 42060, Mexico
Interests: modeling and simulation of electromechanical systems; parameter identification with metaheuristic algorithms; optimization of classical, fuzzy, and neuro-fuzzy controls

Special Issue Information

Dear Colleagues,

This year marks the 24th anniversary of the Academic Area of Engineering and Architecture, which is part of the Institute of Basic Sciences and Engineering at the Autonomous University of the State of Hidalgo. The purpose of this Special Issue is to showcase new ideas and findings related to the development and application of innovative computational and systemic tools for solving complex engineering problems, specifically in the areas of industrial engineering, civil engineering, and urban planning. Our goal is to encourage the modeling, analysis, and resolution of sustainable problems in these fields. We welcome proposals for new analytical methods, probabilistic methods, and optimization metaheuristics for continuous and discrete problems in industrial and civil engineering (but topics are not limited to only these). We also welcome models created with emerging tools such as cellular automata, Petri nets, machine learning, and fuzzy logic for complex engineering problems. Additionally, we seek systemic metaheuristics that can improve organizations and promote sustainable practices for preserving material resources, the environment, urban development, and social welfare.

This upcoming Special Issue is seeking to feature exceptional, unpublished research papers of high quality in the areas of:

  • Emerging computational and systemic methods for modeling, analyzing, and optimizing engineering systems, whether discrete or continuous.
  • Using computational and systemic tools to solve complex engineering problems, focusing on industrial, civil, and urban development sectors.
  • Innovative applications of computational and systemic tools to solve sustainability problems, primarily in the industrial and civil sectors, and the development of sustainable and resilient communities.

Prof. Dr. Juan Carlos Seck Tuoh Mora
Prof. Dr. Liliana Guadalupe Lizárraga-Mendiola
Prof. Dr. Joselito Medina-Marín
Prof. Dr. Norberto Hernández-Romero
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • complex systems
  • mathematical and computational models
  • systemic models
  • civil engineering
  • urbanism
  • industrial engineering
  • systems engineering
  • production and manufacturing systems
  • sustainable urban systems
  • project management
  • logistics
  • flowshop
  • job shop
  • flexible job shop
  • scheduling problems
  • genetic algorithms
  • particle swarm optimization
  • evolutionary algorithms
  • metaheuristics
  • local search
  • cellular automata
  • Petri nets
  • low-impact technologies
  • urban hydrology
  • electromechanical systems
  • parameter identification
  • fuzzy and neuro-fuzzy controls
  • artificial intelligence

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Published Papers (3 papers)

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Editorial

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3 pages, 209 KiB  
Editorial
Engineering and Sustainable Challenges: Latest Advances in Computing and Systemic Tools
by Juan Carlos Seck-Tuoh-Mora, Liliana Lizárraga-Mendiola, Joselito Medina-Marín and Norberto Hernández-Romero
Appl. Sci. 2023, 13(23), 12603; https://doi.org/10.3390/app132312603 - 23 Nov 2023
Viewed by 727
Abstract
Modeling highly nonlinear, coupled systems with a large number of variables is a current challenge in engineering and sustainability [...] Full article

Research

Jump to: Editorial

13 pages, 1301 KiB  
Article
Efficient Task Scheduling Using Constraints Programming for Enhanced Planning and Reliability
by JaeBong Cho, Soonil Jung, Kyungmo Yang, Dohun Kim and WonJong Kim
Appl. Sci. 2024, 14(23), 11396; https://doi.org/10.3390/app142311396 - 6 Dec 2024
Viewed by 435
Abstract
This paper presents an efficient schedule method for maintenance, repair, and overhaul (MRO) tasks for aircraft engines using a constraint programming algorithm. Using data obtained from Korean Air’s MRO maintenance logs, we analyze and predict the optimal scheduling of regular inspections and fault [...] Read more.
This paper presents an efficient schedule method for maintenance, repair, and overhaul (MRO) tasks for aircraft engines using a constraint programming algorithm. Using data obtained from Korean Air’s MRO maintenance logs, we analyze and predict the optimal scheduling of regular inspections and fault repairs for various engine types. By proposing a proper modeling of the problem and preparing data for the constraint programming algorithm, we demonstrate superior performance in scheduling efficiency and resource utilization. The experimental results show an average utilization of 99.35%, and the method can even achieve 100% utilization in some cases. Full article
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12 pages, 2781 KiB  
Article
Modeling Conidiospore Production of Trichoderma harzianum Using Artificial Neural Networks and Response Surface Methodology
by Maria Guadalupe Serna-Diaz, Alejandro Tellez-Jurado, Juan Carlos Seck-Tuoh-Mora, Norberto Hernández-Romero and Joselito Medina-Marin
Appl. Sci. 2024, 14(12), 5323; https://doi.org/10.3390/app14125323 - 20 Jun 2024
Viewed by 790
Abstract
An alternative to facing plagues without affecting ecosystems is the use of biocontrols that keep crops free of harmful organisms. There are some studies showing the use of conidiospores of Trichoderma harzianum as a medium for the biological control of plagues. To find [...] Read more.
An alternative to facing plagues without affecting ecosystems is the use of biocontrols that keep crops free of harmful organisms. There are some studies showing the use of conidiospores of Trichoderma harzianum as a medium for the biological control of plagues. To find the optimal parameters to maximize the production of conidiospores of Trichoderma harzianum in barley straw, this process is modeled in this work through artificial neural networks and response surface modeling. The data used in this modeling include the amount of conidiospores in grams per milliliter, the culture time from 48 to 136 h in intervals of 8 h, and humidity percentages of 70%, 75%, and 80%. The surface response model presents R2 = 0.8284 and an RMSE of 4.6481. On the other hand, the artificial neural network with the best performance shows R2 = 0.9952 and RMSE = 0.7725. The modeling through both methodologies can represent the behavior of the Trichoderma harzianum conidiospores growth in barley straw, showing that the artificial neural network has better goodness of fit than the response surface methodology, and it can be used for obtaining the optimal values for producing conidiospores. Full article
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