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Axioms
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Applied Optimization and Decision Analysis on Interdisciplinary Areas
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Applied Optimization and Decision Analysis on Interdisciplinary Areas

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 9804

Special Issue Editors

Dr. Luis Carlos Méndez González

E-Mail Website
Guest Editor
Department of Industrial Engineering and Manufacturing, Institute of Engineering and Technology, Autonomous University of Ciudad Juárez, Ciudad Juárez 32310, Mexico
Interests: multi-objective optimization; statistical techniques; machine and deep learning; metaheuristics; stochastics process; artificial intelligence and fuzzy techniques; linear and nonlinear programing
Prof. Dr. Luis Alberto Rodríguez-Picón

E-Mail Website
Guest Editor
Department of Industrial Engineering and Manufacturing, Institute of Engineering and Technology, Autonomous University of Ciudad Juárez, Ciudad Juárez 32310, Mexico
Interests: reliability; statistics; degradation; stochastic process; multivariate statistics

Special Issue Information

Dear Colleagues,

Optimization and decision systems have become essential tools in many disciplines whereby practitioners can learn about behavior, demand, and plan improvement strategies for the product under analysis.

We are pleased to invite you to contribute some of your most recent research to this Special Issue, titled “Applied Optimization and Decision Analysis on interdisciplinary areas.”

This Special Issue presents innovative advances covering mathematical optimization and decision techniques and their applications to science and engineering. An applications paper should cover the application of an optimization or decision technique along with the solution of a particular problem. Recent, emerging, and novel areas of optimization, such as machine and deep learning, as well as service system optimization, are encouraged.

Dr. Luis Carlos Méndez-González
Dr. Luis Alberto Rodríguez-Picón
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. Axioms is an international peer-reviewed open access monthly 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

  • multi-objective optimization
  • statistical techniques
  • machine and deep learning
  • metaheuristics
  • stochastics process
  • artificial intelligence and fuzzy techniques
  • linear and nonlinear programing

Published Papers (5 papers)

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Research

24 pages, 2748 KiB  
Article
Using SNAP to Analyze Policy Measures in e-Learning Roadmaps
by Nikola Kadoić, Nina Begičević Ređep and Dragana Kupres
Axioms 2023, 12(12), 1110; https://doi.org/10.3390/axioms12121110 - 11 Dec 2023
Viewed by 1087
Abstract
Creating policy measures is the final step in the process of e-learning roadmap development. Policy measures can be seen as long-term activities that need to be implemented and constantly upgraded to achieve strategic goals. For resource allocation, it is useful to prioritize policy [...] Read more.
Creating policy measures is the final step in the process of e-learning roadmap development. Policy measures can be seen as long-term activities that need to be implemented and constantly upgraded to achieve strategic goals. For resource allocation, it is useful to prioritize policy measures. Prioritization can be implemented using multi-criteria decision-making methods. This paper analyzes policy measures in the Maldives National University’s e-learning roadmap using the social network analysis process (SNAP), which includes the analytic hierarchy process (AHP), the decision-making trial and evaluation laboratory (DEMATEL), and the PageRank centrality. In policy measure evaluation, there were more than 20 participants: persons with managerial functions at the Maldives National University (MNU) (deans, heads of departments) and persons in lecturer and researcher positions. By using the AHP, participants prioritized policy measures with respect to their importance to them. By using the DEMATEL, participants identified and prioritized policy measures with respect to their effect on other measures. Finally, by using the SNAP, it was possible to determine the prioritization list for resource allocation since it aggregates the aspects of the policy measures, their importance, and their effect on other measures. Full article
(This article belongs to the Special Issue Applied Optimization and Decision Analysis on Interdisciplinary Areas)
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13 pages, 2327 KiB  
Article
NIPUNA: A Novel Optimizer Activation Function for Deep Neural Networks
by Golla Madhu, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam M. Zawbaa and Ali Wagdy Mohamed
Axioms 2023, 12(3), 246; https://doi.org/10.3390/axioms12030246 - 28 Feb 2023
Cited by 6 | Viewed by 2926
Abstract
In recent years, various deep neural networks with different learning paradigms have been widely employed in various applications, including medical diagnosis, image analysis, self-driving vehicles and others. The activation functions employed in deep neural networks have a huge impact on the training model [...] Read more.
In recent years, various deep neural networks with different learning paradigms have been widely employed in various applications, including medical diagnosis, image analysis, self-driving vehicles and others. The activation functions employed in deep neural networks have a huge impact on the training model and the reliability of the model. The Rectified Linear Unit (ReLU) has recently emerged as the most popular and extensively utilized activation function. ReLU has some flaws, such as the fact that it is only active when the units are positive during back-propagation and zero otherwise. This causes neurons to die (dying ReLU) and a shift in bias. However, unlike ReLU activation functions, Swish activation functions do not remain stable or move in a single direction. This research proposes a new activation function named NIPUNA for deep neural networks. We test this activation by training on customized convolutional neural networks (CCNN). On benchmark datasets (Fashion MNIST images of clothes, MNIST dataset of handwritten digits), the contributions are examined and compared to various activation functions. The proposed activation function can outperform traditional activation functions. Full article
(This article belongs to the Special Issue Applied Optimization and Decision Analysis on Interdisciplinary Areas)
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20 pages, 2923 KiB  
Article
An Additive Chen Distribution with Applications to Lifetime Data
by Luis Carlos Méndez-González, Luis Alberto Rodríguez-Picón, Ivan Juan Carlos Pérez-Olguín and Luis Ricardo Vidal Portilla
Axioms 2023, 12(2), 118; https://doi.org/10.3390/axioms12020118 - 24 Jan 2023
Cited by 2 | Viewed by 1531
Abstract
This paper presents a lifetime model with properties representing increasing, decreasing, and bathtub curve shapes for failure rates. The proposed model was built based on the additive methodology, for which the Chen distribution was used as the base model, thus introducing the Additive [...] Read more.
This paper presents a lifetime model with properties representing increasing, decreasing, and bathtub curve shapes for failure rates. The proposed model was built based on the additive methodology, for which the Chen distribution was used as the base model, thus introducing the Additive Chen Distribution (AddC). An essential feature of AddC is this model’s excellent flexibility in describing failure rates with non-monotonic behavior or with the shape of a bathtub curve concerning other current models. Statistical properties of AddC are presented and analyzed for different fields of study. For the estimation of AddC’s parameters, the maximum likelihood method (MLE) was used. Three case studies in different fields of application are presented, from which AddC is compared against other probability distributions with similar properties. The results show that AddC offers competitive results. Full article
(This article belongs to the Special Issue Applied Optimization and Decision Analysis on Interdisciplinary Areas)
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14 pages, 3383 KiB  
Article
Performance Assessment of Heuristic Genetic Algorithm (HGA) for Electrochemical Impedance Spectroscopy Parameter Estimation
by Wilian J. Pech-Rodríguez, Gladis G. Suarez-Velázquez, Eddie N. Armendáriz-Mireles, Carlos A. Calles-Arriaga and E. Rocha-Rangel
Axioms 2023, 12(1), 84; https://doi.org/10.3390/axioms12010084 - 13 Jan 2023
Viewed by 1730
Abstract
Due to the importance of cutting-edge nanomaterials applications in energy generation and storage devices, electrochemical impedance spectroscopy (EIS) has been adopted to fully understand the electronic and chemical reactions occurring inside these emerging technologies. Electronic behavior can be correlated with electrochemical properties such [...] Read more.
Due to the importance of cutting-edge nanomaterials applications in energy generation and storage devices, electrochemical impedance spectroscopy (EIS) has been adopted to fully understand the electronic and chemical reactions occurring inside these emerging technologies. Electronic behavior can be correlated with electrochemical properties such as electron transfer resistance, rate of mass diffusion, and the number of electrons in the electrochemical reaction. Although there is a lot of information about the electronic diagrams and methods for parameter estimation, some readers have difficulty analyzing and interpreting EIS curves. Thus, this work proposed using a heuristic approach and genetic algorithms to successfully estimate the resistance and capacitance value of a previously defined circuit model. To assess the potential of the genetic algorithm in electrochemical parameters estimation, we carried out practical measurements with known elements, and then the experimental and theoretical values were compared. Furthermore, the versatility and effectiveness of the algorithm were validated by determining the parameters in an Li-ion battery. The results revealed that the heuristic genetic algorithm (HGA) is a powerful tool for EIS parameters estimation because it can handle large below and upper limits with more pragmatic results in a shorter computational time. Full article
(This article belongs to the Special Issue Applied Optimization and Decision Analysis on Interdisciplinary Areas)
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18 pages, 1021 KiB  
Article
Exploring Role Behavior in Restaurant by Grey Model and Grey Structural Model
by Joyce-Hsiu-Yu Chen, Shu-Hua Wu, Ping-Min Lin and Hsueh-Feng Chang
Axioms 2022, 11(7), 333; https://doi.org/10.3390/axioms11070333 - 9 Jul 2022
Cited by 1 | Viewed by 1397
Abstract
Based on GM (0,N) grey model and grey structure model in grey system theory, this study takes Chinese restaurant in tourist hotel as a case to analyze service role behavior. A total of 241 questionnaires were collected to calculate index weighted coefficients, and [...] Read more.
Based on GM (0,N) grey model and grey structure model in grey system theory, this study takes Chinese restaurant in tourist hotel as a case to analyze service role behavior. A total of 241 questionnaires were collected to calculate index weighted coefficients, and then 12 experts carried out an investigation to construct clusters. There were 12 dimensions of professional competencies, and a total of 50 indicator factors were analyzed for role behavior in a restaurant. According to the results, there are three role behaviors for service staff in Chinese restaurants: supportive, interactive, and integrative role behaviors. In theory, this reinterprets the meaning of catering service competencies and defines the role types of catering service staff. In practical applications, restaurant managers could apply this result to help service staff to understand their current role, in order to reduce their role pressure and to increase their job satisfaction and performance. Full article
(This article belongs to the Special Issue Applied Optimization and Decision Analysis on Interdisciplinary Areas)
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