Jiuping Xu – författare

ISHM is an innovative combination of technologies and methods that offers solutions to the reliability problems caused by increased complexities in design, manufacture, use conditions, and maintenance. Its key strength is in the successful integration of reliability (quantitative estimation of successful operation or failure), "diagnosibility" (ability to determine the fault source), and maintainability (how to maintain the performance of a system in operation). It draws on engineering issues such as advanced sensor monitoring, redundancy management, probabilistic reliability theory, artificial intelligence for diagnostics and prognostics, and formal validation methods, but also "quasi-technical" techniques and disciplines such as quality assurance, systems architecture and engineering, knowledge capture, information fusion, testability and maintainability, and human factors.

This groundbreaking book defines and explains this new discipline, providing frameworks and methodologies for implementation and further research. Each chapter includes experiments, numerical examples, simulations and case studies. It is the ideal guide to this crucial topic for professionals or researchers in aerospace systems, systems engineering, production engineering, and reliability engineering.

This book explores practices and approaches on pre-disaster prevention and post-disaster reconstruction for vulnerable countries and areas enhancing earthquake disaster resilience.

Destructive earthquakes have frequently occurred in urban or rural areas around the world, causing severe damage on human societies. Pre-earthquake prevention and post-earthquake reconstruction effect the disaster resilience building and long-term development of the affected communities and areas. In recent years, researchers from around the world have made a lot of efforts to study on the theme ‘earthquake disaster prevention and reconstruction’.

The chapters in this edited volume contribute to the literature of earthquake disaster research from scientific, social and institutional aspects. These interdisciplinary studies mainly focus on human and policy dimensions of earthquake disaster, such as earthquake risk mitigation, social-physical resilience building, resilience capability assessment, healthcare surge capacity, house reconstruction, the roles of schools, households, civil societies and public participation in earthquake disaster prevention and reconstruction. The authors come from several counties, including China, Bangladesh, Iran, New Zealand, Saudi Arabia, the United Kingdom, Denmark, and Indonesia, covering the cases from those countries prone to earthquakes.

These nine distinctive chapters have been elaborately selected and integrated from the international, ranked, peer-reviewed journal, Environmental Hazards.

This book explores practices and approaches on pre-disaster prevention and post-disaster reconstruction for vulnerable countries and areas enhancing earthquake disaster resilience.

Destructive earthquakes have frequently occurred in urban or rural areas around the world, causing severe damage on human societies. Pre-earthquake prevention and post-earthquake reconstruction effect the disaster resilience building and long-term development of the affected communities and areas. In recent years, researchers from around the world have made a lot of efforts to study on the theme ‘earthquake disaster prevention and reconstruction’.

The chapters in this edited volume contribute to the literature of earthquake disaster research from scientific, social and institutional aspects. These interdisciplinary studies mainly focus on human and policy dimensions of earthquake disaster, such as earthquake risk mitigation, social-physical resilience building, resilience capability assessment, healthcare surge capacity, house reconstruction, the roles of schools, households, civil societies and public participation in earthquake disaster prevention and reconstruction. The authors come from several counties, including China, Bangladesh, Iran, New Zealand, Saudi Arabia, the United Kingdom, Denmark, and Indonesia, covering the cases from those countries prone to earthquakes.

These nine distinctive chapters have been elaborately selected and integrated from the international, ranked, peer-reviewed journal, Environmental Hazards.

Big Data and Information Theory are a binding force between various areas of knowledge that allow for societal advancement. Rapid development of data analytic and information theory allows companies to store vast amounts of information about production, inventory, service, and consumer activities. More powerful CPUs and cloud computing make it possible to do complex optimization instead of using heuristic algorithms, as well as instant rather than offline decision-making.

The era of "big data" challenges includes analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations. Big data calls for better integration of optimization, statistics, and data mining. In response to these challenges this book brings together leading researchers and engineers to exchange and share their experiences and research results about big data and information theory applications in various areas. This book covers a broad range of topics including statistics, data mining, data warehouse implementation, engineering management in large-scale infrastructure systems, data-driven sustainable supply chain network, information technology service offshoring project issues, online rumors governance, preliminary cost estimation, and information system project selection.

The chapters in this book were originally published in the journal, International Journal of Management Science and Engineering Management.

Big Data and Information Theory are a binding force between various areas of knowledge that allow for societal advancement. Rapid development of data analytic and information theory allows companies to store vast amounts of information about production, inventory, service, and consumer activities. More powerful CPUs and cloud computing make it possible to do complex optimization instead of using heuristic algorithms, as well as instant rather than offline decision-making.

The era of "big data" challenges includes analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations. Big data calls for better integration of optimization, statistics, and data mining. In response to these challenges this book brings together leading researchers and engineers to exchange and share their experiences and research results about big data and information theory applications in various areas. This book covers a broad range of topics including statistics, data mining, data warehouse implementation, engineering management in large-scale infrastructure systems, data-driven sustainable supply chain network, information technology service offshoring project issues, online rumors governance, preliminary cost estimation, and information system project selection.

The chapters in this book were originally published in the journal, International Journal of Management Science and Engineering Management.

This book offers a comprehensive exploration of the latest advancements in sustainable and resilient supply chain management. The chapters in this volume present a diverse range of topics, including innovative strategies for optimizing sustainable food supply chains through data envelopment analysis, dynamic multi-modal perspectives on global supply chain network configuration, and robust data-driven optimization techniques for designing sustainable cold supply chains for livestock and perishable goods. Other chapters delve into key areas such as optimal pricing and production lot size strategies for sustainable inventory models, carbon-sensitive transport solutions for deteriorating supply chains, and trade credit policies in growing product supply chains.

Additionally, the book addresses the complexities of inventory management, purchasing, and cutting policies for imperfect and perishable raw materials, the influence of supply chain finance and trade digitization on financial stability, and the development of heuristic master planning algorithms that prioritize fairness and flexibility. Further studies examine adaptive product changeover policies, a PDCA-based approach to evaluating green supply chain performance, and robust multi-criteria decision analysis techniques for selecting transportation service providers in the face of uncertainty. By offering insights into both theoretical and practical aspects, this book provides a valuable resource for researchers, practitioners, and policymakers looking to navigate the evolving landscape of sustainable supply chains. This book will be valuable to students, researchers and policymakers in the fields of supply chain management, sustainable logistics and operations research.

The chapters in this book were originally published in International Journal of Management Science and Engineering Management.

This book offers a comprehensive exploration of the latest advancements in sustainable and resilient supply chain management. The chapters in this volume present a diverse range of topics, including innovative strategies for optimizing sustainable food supply chains through data envelopment analysis, dynamic multi-modal perspectives on global supply chain network configuration, and robust data-driven optimization techniques for designing sustainable cold supply chains for livestock and perishable goods. Other chapters delve into key areas such as optimal pricing and production lot size strategies for sustainable inventory models, carbon-sensitive transport solutions for deteriorating supply chains, and trade credit policies in growing product supply chains.

Additionally, the book addresses the complexities of inventory management, purchasing, and cutting policies for imperfect and perishable raw materials, the influence of supply chain finance and trade digitization on financial stability, and the development of heuristic master planning algorithms that prioritize fairness and flexibility. Further studies examine adaptive product changeover policies, a PDCA-based approach to evaluating green supply chain performance, and robust multi-criteria decision analysis techniques for selecting transportation service providers in the face of uncertainty. By offering insights into both theoretical and practical aspects, this book provides a valuable resource for researchers, practitioners, and policymakers looking to navigate the evolving landscape of sustainable supply chains. This book will be valuable to students, researchers and policymakers in the fields of supply chain management, sustainable logistics and operations research.

The chapters in this book were originally published in International Journal of Management Science and Engineering Management.

This book presents a cohesive collection of cutting-edge research focused on advanced decision-support methodologies for complex and ambiguous operational contexts. This volume systematically assembles ten pivotal studies employing uncertain decision-making, multi-criteria decision analysis (MCDA), and tailored optimization models to address substantive challenges in supply chain management, sustainable operations, and strategic planning.

The contributions span a rigorous methodological spectrum, including fuzzy PDCA cycles for green performance evaluation, hybrid MCDM frameworks for lean tool selection, and robust optimization for resilient network design. Applications are drawn from critical domains such as healthcare logistics during epidemic response, sustainable supply chain configuration, and large-scale project trade-off analysis under resource constraints. Each chapter demonstrates the translation of theoretical computational models into applied solutions for decision-making under volatility, incomplete information, and multi-objective pressures.

This volume will serve as a significant reference for academics and graduate researchers in management science, operations research, and industrial engineering. It provides a structured examination of how contemporary soft computing and operational research techniques can be leveraged to enhance analytical rigor and strategic outcomes in the face of pervasive environmental uncertainty.

The chapters in this book were published in International Journal of Management Science and Engineering Management.

This book presents a cohesive collection of cutting-edge research focused on advanced decision-support methodologies for complex and ambiguous operational contexts. This volume systematically assembles ten pivotal studies employing uncertain decision-making, multi-criteria decision analysis (MCDA), and tailored optimization models to address substantive challenges in supply chain management, sustainable operations, and strategic planning.

The contributions span a rigorous methodological spectrum, including fuzzy PDCA cycles for green performance evaluation, hybrid MCDM frameworks for lean tool selection, and robust optimization for resilient network design. Applications are drawn from critical domains such as healthcare logistics during epidemic response, sustainable supply chain configuration, and large-scale project trade-off analysis under resource constraints. Each chapter demonstrates the translation of theoretical computational models into applied solutions for decision-making under volatility, incomplete information, and multi-objective pressures.

This volume will serve as a significant reference for academics and graduate researchers in management science, operations research, and industrial engineering. It provides a structured examination of how contemporary soft computing and operational research techniques can be leveraged to enhance analytical rigor and strategic outcomes in the face of pervasive environmental uncertainty.

The chapters in this book were published in International Journal of Management Science and Engineering Management.

High temperature, high oil pressure, oil and gas well completion testing have always been a technical challenge and basic theoretical research is one of the key factors needed to ensure a successful completion test. The completion test basic theory includes: a stress analysis of the completion string, completion string buckling behavior, and temperature and pressure distribution prediction. The completion string is the main bearing and power transmission component for oil and gas well operations and production, and it is required to take on a combination of loads, which result in completion string deformation. Because of these complex relationships, completion string stress analysis has become increasingly more complicated.

This book discusses the characters of tubular strings in HTHP (High Temperature - High Pressure) oil and gas wells. These characters include the mechanical behavior of tubular strings and the temperature and pressure variation of tubular strings in different conditions. Mathematical models are established for different conditions and solution existence and uniqueness of some models is discussed, providing algorithms corresponding to the different models. Numerical experiments are presented to verify the validity of models and the feasibility of algorithms, and the impact of the parameters of models for oil and gas wells is also discussed.

This book is written for production and testing engineers to provide them with the tools to deal more effectively with the numerical decisions they have to take and for researchers and technicians in petroleum and gas testing and production engineering. Finally, it is also intended to serve as a reference book for mathematicians, college teachers and students.

High temperature, high oil pressure, oil and gas well completion testing have always been a technical challenge and basic theoretical research is one of the key factors needed to ensure a successful completion test. The completion test basic theory includes: a stress analysis of the completion string, completion string buckling behavior, and temperature and pressure distribution prediction. The completion string is the main bearing and power transmission component for oil and gas well operations and production, and it is required to take on a combination of loads, which result in completion string deformation. Because of these complex relationships, completion string stress analysis has become increasingly more complicated.

This book discusses the characters of tubular strings in HTHP (High Temperature - High Pressure) oil and gas wells. These characters include the mechanical behavior of tubular strings and the temperature and pressure variation of tubular strings in different conditions. Mathematical models are established for different conditions and solution existence and uniqueness of some models is discussed, providing algorithms corresponding to the different models. Numerical experiments are presented to verify the validity of models and the feasibility of algorithms, and the impact of the parameters of models for oil and gas wells is also discussed.

This book is written for production and testing engineers to provide them with the tools to deal more effectively with the numerical decisions they have to take and for researchers and technicians in petroleum and gas testing and production engineering. Finally, it is also intended to serve as a reference book for mathematicians, college teachers and students.

Welcome to the proceedings of the Sixth International Conference on Management Science and Engineering Management (ICMSEM2012) held from November 11 to 14, 2012 at Quaid-i-Azam University, Islamabad, Pakistan and supported by Sichuan University (Chengdu, China), Quaid-i-Azam University (Islamabad, Pakistan) and The National Natural Science Foundation of China. The International Conference on Management Science and Engineering Management is the annual conference organized by the International Society of Management Science and Engineering Management. The goals of the Conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current research results.

The papers are classified into 8 sections: Computer and Networks, Information Technology, Decision Support System, Industrial Engineering, Supply Chain Management, Project Management, Manufacturing and Ecological Engineering. The key issues of the sixth ICMSEM cover various areas in MSEM, such as Decision Support System, Computational Mathematics, Information Systems, Logistics and Supply Chain Management, Relationship Management, Scheduling and Control, Data Warehousing and Data Mining, Electronic Commerce, Neural Networks, Stochastic models and Simulation, Heuristics Algorithms, Risk Control, and Carbon Credits.