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Mathematics
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Network Reliability and Optimization of Industrial Engineering and Management
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Network Reliability and Optimization of Industrial Engineering and Management

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 2805

Special Issue Editors

Prof. Dr. Yi-Kuei Lin

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Guest Editor
Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu City 300093, Taiwan
Interests: network reliability; intellectual manufacturing; machine learning; green resilience supply chain; dynamic quality management; service science and management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Cheng-Ta Yeh

E-Mail Website
Guest Editor
Department of Information Management, Fu Jen Catholic University, New Taipei City 242062, Taiwan
Interests: network reliability analysis; metaheuristics; system optimization; service quality analysis
Prof. Dr. Ping-Chen Chang

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan
Interests: network reliability; manufacturing management; simulation

Special Issue Information

Dear Colleagues,

Our upcoming Special Issue entitled "Network Reliability and Optimization in Industrial Engineering and Management" seeks to bridge the realms of mathematics and industrial applications by focusing on the critical role of network reliability and optimization in enhancing industrial and expert systems. Industrial engineering and management are at the core of modern production and service systems, and the mathematical underpinnings of reliability and optimization are paramount in ensuring efficiency, quality, and sustainability.

We welcome the submission of research publications that delve into the mathematical foundations of network reliability, offering novel methodologies and models for assessing and improving the robustness of industrial systems. We also welcome submissions in the form of works that explore mathematical optimization techniques to enhance decision-making processes, cost efficiency, and resource allocation in industrial settings. We aim to bring together mathematical rigor and real-world relevance, fostering discussions that advance the field of industrial engineering and management, making it more resilient and effective. Researchers are encouraged to submit their cutting-edge work to contribute to the synergy between mathematics and industry. This Special Issue will cover a wide range of topics, including but not limited to the following:

  • Network reliability analysis and modeling;
  • The optimization of industrial engineering in network analysis;
  • Reliability-centered maintenance;
  • Resilience analysis in practical systems;
  • Multi-objective optimization in industrial engineering with reliability;
  • Machine Learning (ML) and optimization in industrial engineering and management;
  • Sustainability and green operations in networks;
  • Network risk assessment and management;
  • Network security and vulnerability;
  • Supply chain management in network reliability.

Prof. Dr. Yi-Kuei Lin
Prof. Dr. Cheng-Ta Yeh
Prof. Dr. Ping-Chen Chang
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. Mathematics 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 2600 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

  • network reliability
  • optimization
  • industrial engineering and management
  • decision making
  • mathematical models

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

21 pages, 1149 KiB  
Article
Supply Chain Analysis Based on Community Detection of Multi-Layer Weighted Networks
by Yingqiu Zhu, Ruiyi Wang, Mingfei Feng, Lei Qin, Ben-Chang Shia and Ming-Chih Chen
Mathematics 2024, 12(22), 3606; https://doi.org/10.3390/math12223606 - 19 Nov 2024
Viewed by 400
Abstract
As the economic environment becomes more complex, improving supply chain resilience is critical for the effective operation and long-term sustainability of businesses. Real-world supply chains, which consist of various components such as goods, warehouses, and plants, often feature intricate network structures that pose [...] Read more.
As the economic environment becomes more complex, improving supply chain resilience is critical for the effective operation and long-term sustainability of businesses. Real-world supply chains, which consist of various components such as goods, warehouses, and plants, often feature intricate network structures that pose challenges for resilience analysis. This paper addresses these challenges by proposing a framework for studying supply chains using multi-layer network community detection. The complex multi-mode supply chain network is transformed into single-mode, multi-layer weighted networks. A multi-layer weighted community detection method is proposed for identifying local clusters within these networks, revealing interconnected groups that highlight flexibility and redundancy in production capabilities across different plants and goods. An empirical study utilizing real data demonstrates that this clustering method effectively detects indirect capacity links between plants and goods. The insights derived from this method are useful for strategic capacity management, allowing businesses to respond more effectively to supply shortages and unexpected increases in demand. Full article
(This article belongs to the Special Issue Network Reliability and Optimization of Industrial Engineering and Management)
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30 pages, 2023 KiB  
Article
A Network Reliability Analysis Method for Complex Real-Time Systems: Case Studies in Railway and Maritime Systems
by Yu Zang, Jiaxiang E and Lance Fiondella
Mathematics 2024, 12(19), 3014; https://doi.org/10.3390/math12193014 - 27 Sep 2024
Viewed by 1105
Abstract
The analysis of complex system reliability is an area of growing interest, particularly given the diverse and intricate nature of the subsystems and components these systems encompass. Tackling the reliability of such multifaceted systems presents challenges, including component wear, multiple failure modes, the [...] Read more.
The analysis of complex system reliability is an area of growing interest, particularly given the diverse and intricate nature of the subsystems and components these systems encompass. Tackling the reliability of such multifaceted systems presents challenges, including component wear, multiple failure modes, the cascading effects of these failures, and the associated uncertainties, which require careful consideration. While traditional studies have examined these elements, the dynamic interplay of information between subsystems and the overarching system has only recently begun to draw focus. A notably understudied aspect is the reliability analysis of complex real-time systems that must adapt to evolving operational conditions. This paper proposes a novel methodology for assessing the reliability of complex real-time systems. This method integrates complex network theory, thus capturing the intricate operational characteristics of these systems, with adjustments to several key complex network parameters to define the nuances of communication within the network framework. To showcase the efficacy and adaptability of our approach, we present case studies on railway and maritime systems. For the railway system, our analysis spans various operational scenarios: from single train operations to simultaneous operations across multiple or different radio block center regions, accounting for node and edge failures. In maritime systems, the case studies employing the VHF data exchange system under operational scenarios are subject to network reliability analysis, successfully pinpointing critical vulnerabilities and modules of high importance. The findings of our research are promising, demonstrating that the proposed method not only accurately evaluates the overall reliability of complex systems but also identifies the pivotal weak points—be it modules or links—warranting attention for system enhancement. Full article
(This article belongs to the Special Issue Network Reliability and Optimization of Industrial Engineering and Management)
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16 pages, 1711 KiB  
Article
Fuzzy Evaluation Model for Lifetime Performance Using Type-I Censoring Data
by Kuo-Ching Chiou, Tsun-Hung Huang, Kuen-Suan Chen and Chun-Min Yu
Mathematics 2024, 12(13), 1935; https://doi.org/10.3390/math12131935 - 21 Jun 2024
Cited by 1 | Viewed by 803
Abstract
As global warming becomes increasingly serious, humans start to consider how to coexist with the natural environment. People become more and more aware of environmental protection and sustainable development. Therefore, in the pursuit of economic growth, it has become a consensus that enterprises [...] Read more.
As global warming becomes increasingly serious, humans start to consider how to coexist with the natural environment. People become more and more aware of environmental protection and sustainable development. Therefore, in the pursuit of economic growth, it has become a consensus that enterprises should be responsible for the social and ecological environment. Regarding the manufacturing of electronic devices, as long as both component production quality and assembly quality are ensured, consumers can be provided with high-quality, safe, and efficient products. In light of this trend, enhancing product availability and reliability can reduce costs and carbon emissions resulting from repairing or replacing components, thus becoming a vital factor for corporate and environmental sustainability. Accordingly, enterprises enhance their economic benefits as well as have the effects of energy conservation and waste reduction by extending products’ service lifetime and increasing their added value. According to several studies, it takes a long time to retrieve electronic products’ lifetime data. Moreover, acquiring complete samples is often challenging. Consequently, when analyzing real cases, samples are usually collected using censoring techniques. The type-I right censoring data is suitable for industrial processes. Thus, this study utilized type-I right censoring sample data to estimate the lifetime performance index. It usually takes a large amount of time to access lifetime data for electronic products and it is often impossible to obtain complete samples since the size of the sample is usually small. Hence, to avoid misjudgment caused by sampling errors, this study followed suggestions from existing research and applied fuzzy tests built on confidence intervals to establish a fuzzy evaluation model for the lifetime performance index. This model helps relevant electronic industries not only evaluate the lifetime of their electronic components but also instantly seize opportunities for improvement. Full article
(This article belongs to the Special Issue Network Reliability and Optimization of Industrial Engineering and Management)
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