{"title":"Foreword to the Special Issue on Mathematical Methods in Reliability (MMR23)","authors":"Félix Belzunce, Jorge Navarro","doi":"10.1002/asmb.2894","DOIUrl":null,"url":null,"abstract":"<p>The 12th International Conference on Mathematical Methods in Reliability (MMR 2023, May 30–June 2, Murcia Spain) continues a distinguished tradition of bringing together leading experts, researchers, and practitioners from various fields to explore cutting-edge advancements in reliability theory and applications. Since its inception, the MMR conference series has provided a premier platform for exchanging ideas and promoting collaboration across a wide array of disciplines, including mathematics, engineering, statistics, operations research, and computer science.</p><p>Reliability theory plays a crucial role in designing and analyzing complex systems, where safety, dependability, and risk assessment are paramount. As technological advancements accelerate and systems become increasingly intricate, the demand for robust mathematical models and methods to ensure system reliability is more critical than ever.</p><p>As the world faces new challenges in ensuring the resilience and reliability of critical infrastructures and technologies, the MMR conference continues to inspire innovation and foster collaboration. We hope this collection of papers will provide readers with valuable insights and stimulate further research in this vibrant and essential field.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 5","pages":"1206-1208"},"PeriodicalIF":1.3000,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2894","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Stochastic Models in Business and Industry","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/asmb.2894","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
The 12th International Conference on Mathematical Methods in Reliability (MMR 2023, May 30–June 2, Murcia Spain) continues a distinguished tradition of bringing together leading experts, researchers, and practitioners from various fields to explore cutting-edge advancements in reliability theory and applications. Since its inception, the MMR conference series has provided a premier platform for exchanging ideas and promoting collaboration across a wide array of disciplines, including mathematics, engineering, statistics, operations research, and computer science.
Reliability theory plays a crucial role in designing and analyzing complex systems, where safety, dependability, and risk assessment are paramount. As technological advancements accelerate and systems become increasingly intricate, the demand for robust mathematical models and methods to ensure system reliability is more critical than ever.
As the world faces new challenges in ensuring the resilience and reliability of critical infrastructures and technologies, the MMR conference continues to inspire innovation and foster collaboration. We hope this collection of papers will provide readers with valuable insights and stimulate further research in this vibrant and essential field.
期刊介绍：
ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process.
The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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