Operationsanalyse

This book provides a systematic presentation of the major results in the field of the theory of k-out-of-n systems obtained in recent years and their applications for the reliability assessment of high-altitude unmanned platforms. Mathematical models, methods, and algorithms, presented in the book, will make a significant contribution to the development of reliability theory and the theoretical foundations of unmanned UAV-based aerial communications networks in the framework of the concept of creating the 5G and beyond networks. The book gives a description of new mathematical methods and approaches (based on decomposable semi-regenerative processes, simulation and machine learning methods, and inventory models) to the study of the complex k-out-of-n systems, which makes it possible to carry out numerical calculations of reliability indicators. Organized into five chapters, each chapter begins with a summary of the main definitions andresults contained in the chapter. The content of this book is based on the original results developed by the authors, many of which appear for the first time in book form.

The Evolution of Immunotherapy Against Tumors: An Historical Approach summarizes the literature concerning the development of the theory of immune surveillance against tumors. It discusses the evidence for and against this theory, along with the concept of immunoediting. Finally, current approaches in anti-tumor immunotherapy will be analyzed. The immune system plays a major role in the surveillance against tumors. To avoid attack from the immune system, tumor cells develop different strategies to escape immune surveillance. Evidence of immune surveillance comes from both animal models and clinical observations. Mice with a wide variety of immunodeficiencies have a high rate of tumor incidence and are more susceptible to transplanted or chemical carcinogen-induced tumors. Immunosuppressed patients have a high incidence of tumors. However, many patients develop cancer even in the presence of an apparently normal immune system. This indicates that tumor cells can escape immune surveillance.

Intelligence Systems for Earth, Environmental and Planetary Sciences: Methods, Models and Applications provides cutting-edge theory and applications of modern-day artificial intelligence and data science in the Earth, environment, and planetary science fields. The book is divided into three sections: (i) Methods, covering the fundamentals of intelligence systems, along with an introduction to the preparation of datasets; (ii) Models, detailing model development, data assimilation, and techniques in each field; and (iii) Applications, presenting case studies of artificial intelligence and data science solutions to Earth, environmental, and planetary sciences problems, as well as future perspectives. Intelligence Systems for Earth, Environmental and Planetary Sciences will be of interest to students, academics, and postgraduate professionals in the field of applied sciences, Earth, environmental, and planetary sciences and would also serve as an excellent companion resource to courses studying artificial intelligence applications for theoretical and practical studies in Earth, environmental, and planetary sciences.

This unique textbook explicitly addresses the intersection of advanced analytics and procurement. It is motivated by one core question: How can firms generate (economic) value from procurement data? It demonstrates that procurement is one of the major functions within a firm where data analytics, artificial intelligence, and operations research can successfully be leveraged to reduce cost and risk and to achieve resilience and sustainability goals.The book provides a methods-based overview of data-driven optimization of purchasing decisions. Besides presenting key concepts and applications, it particularly focuses on implementation, so as to help (future) procurement managers and data scientists quickly evaluate the value generated by a given data-driven solution. What sets this textbook apart is its combination of rigorous, state-of-the-art methodologies from academic research and first-hand experience from various application-oriented consulting projects in a range ofindustries. Though primarily intended for graduate students with a major in procurement and supply chain management, the book will also benefit purchasing managers with and without specific knowledge of advanced analytics techniques, and data scientists with and without specific experience in procurement.

This book introduces the fundamentals of probability, statistical, and reliability concepts, the classical methods of uncertainty quantification and analytical reliability analysis, and the state-of-the-art approaches of design optimization under uncertainty (e.g., reliability-based design optimization and robust design optimization). The topics include basic concepts of probability and distributions, uncertainty quantification using probabilistic methods, classical reliability analysis methods, time-variant reliability analysis methods, fundamentals of deterministic design optimization, reliability-based design optimization, robust design optimization, other methods of design optimization under uncertainty, and engineering applications of design optimization under uncertainty.

This proceedings volume gathers selected, blinded peer-reviewed contributions presented at the XXIX International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM), held in Lisbon, Portugal, from June 28th to 30th, 2023.This volume focuses especially on the applications of Industrial Engineering and Operations Management for research and practice. It includes relevant information for academics since most of the chapters focus on real-world case studies and systematic reviews. It also provides valuable insights for professionals in the industrial sector by presenting solutions to complex industrial challenges.The 2023 iteration of the IJCIEOM conference had the theme "Developing resilience in Industrial Engineering and Operations Management" and aimed to analyze the resilience of supply chains in the post-COVID-19 era. The works published in this volume focus on how Digital Transformation (DX) and Artificial Intelligence (AI) have made themanufacturing and service industry more resistant to VUCA elements (i.e., volatile, uncertain, complex, and ambiguous). Regarding DX and AI, the research specifically focused on supply chain management, project management, and Industry 4.0. Other studies explore how industrial engineering incorporated innovative and technological concepts into service and product operations. Overall, this volume provides a valuable resource for researchers and practitioners alike as it presents numerous relevant contributions in identifying new challenges and opportunities for industrial engineering and operations management.This conference was sponsored by renowned international industry engineering associations, particularly the American Society for Engineering Management (ASEM), the Institute of Industrial & Systems Engineers (IISE), and the Asociación para el Desarrollo de la Ingeniería de Organización (ADINGOR).

This contributed volume explores innovative research in the modeling, simulation, and control of crowd dynamics. Chapter authors approach the topic from the perspectives of mathematics, physics, engineering, and psychology, providing a comprehensive overview of the work carried out in this challenging interdisciplinary research field. The volume begins with an overview of analytical problems related to crowd modeling. Attention is then given to the importance of considering the social and psychological factors that influence crowd behavior ¿ such as emotions, communication, and decision-making processes ¿ in order to create reliable models. Finally, specific features of crowd behavior are explored, including single-file traffic, passenger movement, modeling multiple groups in crowds, and the interplay between crowd dynamics and the spread of disease.Crowd Dynamics, Volume 4 is ideal for mathematicians, engineers, physicists, and other researchers working in the rapidly growing field of modeling and simulation of human crowds.

This book showcases recent research advances in service science and related fields. Including selected papers from the 2022 INFORMS International Conference on Service Science, held in Shenzhen, China from July 2 to 4, 2022, the book presents new theories and empirical results in the emerging, interdisciplinary field of digital transformation and society. Incorporating research, education and practice alike, the respective chapters highlight a host of ways to approach these challenges in service science.

Logistics and supply chain management is facing disruptive economic, technological and climate change developments that require new strategies. New technologies such as the Internet-of-Things, digital manufacturing or blockchain are emerging quickly and could provide competitive advantage to those companies that leverage the technologies smartly while managers that do not adopt and embrace change could be left behind. Last but perhaps most important for mankind, sustainability aspects such as low-carbon transportation, closed loop supply chains or socially-responsible supply chain setups will become essential to operate successfully in the future. All these aspects will affect logistics and supply chains as a whole as well as different functional areas such as air cargo, maritime logistics or sourcing/procurement.This book aims to dive into several of these functional topics to highlight the key developments in the next decade predicted by leading global experts in the field. It features contributions and key insights of globally leading scholars and senior industry experts. Their forward-looking perspectives on the anticipated trends are aimed at informing the reader about how logistics and supply chain management will evolve in the next decade and which academic qualities and skills will be required to succeed in the "e;new normal"e; environment that will be characterized by volatile and increasingly disrupted business eco-systems. Future scenarios are envisaged to provide both practitioners and students with insights that will help them to adapt and succeed in a fast changing world.

This book presents a curated selection of recent research in functional analysis and fixed-point theory, exploring their applications in interdisciplinary fields. The primary objective is to establish a connection between the latest developments in functional analysis and fixed-point theory and the broader interdisciplinary research landscape. By doing so, this book aims to address the needs of researchers and experts seeking to stay up-to-date with the cutting-edge research trends in functional analysis, fixed-point theory and related areas. It also aims to pave the way for applying functional analysis and fixed-point theory to solve interdisciplinary problems in various domains, including but not limited to fractional calculus, integral equations, queuing theory, convex analysis, harmonic analysis and wavelet analysis.

This book presents an extension of fuzzy set theory allowing for multi-polar information, discussing its impact on the theoretical and practical development of multi-criteria decision making. It reports on set of hybrid models developed by the authors, and show how they can be adapted, case by case, to the lack of certainty under a variety of criteria. Among them, hybrid models combining m-polar fuzzy sets with rough, soft and 2-tuple linguistic sets, and m-polar hesitant fuzzy sets and hesitant m-polar fuzzy are presented, together with some significant applications. In turn, outranking decision-making techniques such as m-polar fuzzy ELECTRE I, II, III and IV methods, as well as m-polar fuzzy PROMETHEE I and II methods, are developed. The efficiency of these decision-making procedures, as well as other possible extensions studied by the authors, is shown in some real-world applications. Overall, this book offers a guide on methodologies to deal with the multi-polarity and fuzziness of the real-world problems, simultaneously. By including algorithms and computer programming codes, it provides a practice-oriented reference guide to both researchers and professionals working at the interface between computational intelligence and decision making.

Circular economy can serve as a key building block for the sustainability targets of manufacturing companies. Although the term itself has long been established, we see that proper implementation of a circular economy model across entire manufacturing value chains is still lacking and remains a challenge. However, there are clearly visible and good examples of circular economy standards which have already been applied and are generating value among multiple layers. Circular Economy and Manufacturing presents these and more, providing a roadmap of optimized, flexible, efficient, effective, and competitive green production strategies for the manufacturing industry and its multiple stakeholders. The volume proves to be an excellent springboard for further discussion and research into new frameworks of best practices in view of achieving more socially responsible and sustainable organizations in a not-so-distant future.

Therapeutic Applications of Nitric Oxide in Cancer and Inflammatory Disorders: Third International Conference on Therapeutic Application of Nitric Oxide in Cancer and Inflammatory Disorders presents updated information on the chemistry, signaling of newly derived therapeutic nitric oxide donors/inhibitors, and their complexes in liposomes or nanospheres in both preclinical and clinical investigations.This book consists of the following: The program and abstracts presented at the Third International Conference in Udine, Italy, September 3-5, 2023; Parts I-V review on (I) the general properties of nitric oxide in diseases; (II) the role of nitric oxide in cancer; (III) nitric oxide and immunity; (IV) nitric oxide and aging; and (V) nitric oxide and therapeutics. In addition, part VI is an educational review on artificial intelligence and its application in diseases. These updated reviews present many examples of research investigations related to the application of novel therapeutic compounds on nitric oxide and new derivatives, as well as their significant therapeutic activities against various resistant cancers that are unresponsive to current treatments and in different inflammatory disorders.This book is a valuable resource for cancer researchers, oncologists, graduate students, and investigators from medical and biomedical fields who want to learn more about NO and its therapeutic applications in cancer and inflammatory diseases. This book is also highly useful for both clinicians and oncologists as well as pharmaceutical companies involved in the development of new anticancer/antiinflammatory agents.

"Demystifies AI for business professionals, highlighting its strengths, weaknesses, and real-world applications, while providing actionable insights for responsible implementation and risk mitigation"--

This textbook provides a comprehensive overview of noncooperative and cooperative dynamic games involving uncertain parameter values, with the stochastic process being described by an event tree. Primarily intended for graduate students of economics, management science and engineering, the book is self-contained, as it defines and illustrates all relevant concepts originally introduced in static games before extending them to a dynamic framework. It subsequently addresses the sustainability of cooperative contracts over time and introduces a range of mechanisms to help avoid such agreements breaking down before reaching maturity. To illustrate the concepts discussed, the book provides various examples of how dynamic games played over event trees can be applied to environmental economics, management science, and engineering.

The book explores cost-effective and efficient supply chain management to achieve resilience in the post-COVID environment. Qualitative, quantitative, case studies, and systematic literature reviews are made in the book. The book follows a didactic approach through which it informs global researchers and practitioners to deal with the most significant insights on future supply chains with a more in-depth analysis of post-COVID opportunities and challenges. In particular, this book provides an in-depth assessment of disruptive supply chain management in certain industrial contexts and explores various Industry 4.0 and Industry 5.0 technologies to achieve resilience.The book is used as a supplemental textbook for study within university level programs, at late undergraduate and graduate levels, in faculties of business and management, engineering systems, information systems, education, and computing.

This book is the first comprehensive guide to logic-based Benders decomposition (LBBD), a general and versatile method for breaking large, complex optimization problems into components that are small enough for practical solution. The author introduces logic-based Benders decomposition for optimization, which substantially generalizes the classical Benders method. It can reduce solution times by orders of magnitude and allows decomposition to be applied to a much wider variety of optimization problems. On the theoretical side, this book provides a full account of inference duality concepts that underlie LBBD, as well as a description of how LBBD can be combined with stochastic and robust optimization, heuristic methods, and decision diagrams. It also clarifies the connection between LBBD and combinatorial Benders cuts for mixed integer programming. On the practical side, it explains how LBBD has been applied to a rapidly growingvariety of problem domains. After describing basic theory, this book provides a comprehensive review of the rapidly growing literature that describes these applications, in each case explaining how LBBD is adapted to the problem at hand. In doing so this work provides a sourcebook of ideas for applying LBBD to new problems as they arise.

In this book, the concept of a hypothesis about the values of all attributes is added to the standard decision tree model, considered, in particular, in test theory and rough set theory. This extension allows us to use the analog of equivalence queries from exact learning and explore decision trees that are based on various combinations of attributes, hypotheses, and proper hypotheses (analog of proper equivalence queries). The two main goals of this book are (i) to provide tools for the experimental and theoretical study of decision trees with hypotheses and (ii) to compare these decision trees with conventional decision trees that use only queries, each based on a single attribute. Both experimental and theoretical results show that decision trees with hypotheses can have less complexity than conventional decision trees. These results open up some prospects for using decision trees with hypotheses as a means of knowledge representation and algorithms for computing Boolean functions. The obtained theoretical results and tools for studying decision trees with hypotheses are useful for researchers using decision trees and rules in data analysis. This book can also be used as the basis for graduate courses.

This book provides insights from research and practice in how organizations were able to sustain resilience in their global supply chains during the COVID-19 pandemic and to advance the understanding of supply chain risk management. The chapters highlight the lessons learned, insist on new models for resilience, suggest improved supply chain risk methodologies and bridge the gap between research and practice. It helps readers acquire greater knowledge, strategic approaches, new methods, and practical tools for ensuring global supply chain resilience.

This book explains ¿what goes on in a manufacturing company as a product goes through its lifecycle¿. It describes more than 70 product-related activities that take place during the product lifecycle phases of ideation, development, production, service, and recycling. The various documents, data, working methods, and computer programs used in each activity are outlined. The book tells the story of a project carried out by a Master¿s degree student in a manufacturing company to find out for the CEO exactly what happens with products across their lifecycle. Due to the storytelling approach of the book, the reader will learn, as if they are present in the company, about the activities that take place along the product lifecycle. They will see how the company is organized, what data and documents are created and used in each activity, and which applications are being used. They will see, from the interviews carried out by the student, what people are doing, the difficulties they face, and the improvement opportunities they see. This will give them a good understanding of the various activities that take place, and provide a basis for improving performance and implementing new processes and applications.

This book presents contributions to the 50th Annual Conference of the Operations Research Society of South Africa (ORSSA), which was jointly hosted with the African Federation of Operations Research Societies (AFROS) at North-West University in Potchefstroom, South Africa from 12 to 15 September, 2021. Focusing on innovative case studies and recent applications of Operations Research models and algorithms in African countries, each chapter highlights findings emerging from the countries in question and explains the lessons learned. As such, the book offers an up-to-date overview of Operations Research practices and developments in Africa. AFROS is a "e;not for profit"e; organization that aims to promote Operations Research in Africa. Its affairs are regulated by an Executive Committee consisting of representatives/alternates of all its member societies. The members of the Federation undertake to co-operate in the advancement of knowledge, interest and education in Operations Research by appropriate means, particularly the exchange of information, the holding of meetings and conferences, and the awarding of prizes.

This book aims to stimulate debate in the growing and highly controversial area of measuring scholarly work. The authors examine key aspects of this topic through the lens of the latest theoretical developments in service science and associated fields. It includes chapters explaining the theoretical developments and methodological aspects of measuring the quality of academic teaching and research, while other chapters provide a review and analysis of various types of scholarly work metrics and processes with examples from several countries, cultures, and educational systems. The current growing concern about higher education (HE) quality has prompted institutions to divide university teachers' work into different areas and to design methods aimed at measuring the productivity of these areas. It is widely accepted that the need to evaluate HE service quality is a relevant issue for any society. However, the authors argue that most of the current practices used in the pursuit of this objective are jeopardizing the future of the university as a place of knowledge generation, science evolution and professional education.

This book addresses the growing need for a standard textbook on input-output analysis (IO) within the context of industrial ecology (IE). IE is a discipline dedicated to providing system-wide, quantitative, and science-based solutions for sustainable development challenges, and its global importance has been rapidly increasing. The primary analytical tools of IE are life-cycle assessment (LCA) and material flow analysis (MFA). IO has been widely utilized for LCA since the late 1990s and is increasingly being applied to MFA as well. This trend is being driven by the greater availability and application of global IO data, which now includes an ever-expanding number of countries and regions. Despite the presence of excellent textbooks on IO and IE individually, there is a lack of resources that integrate these two fields. This book seeks to fill that gap by focusing on the practical application of IO to IE, specifically in the context of LCA and MFA. By combining these methodologies, readers can gain valuable insights into sustainable development issues and contribute to more effective solutions in the field of IE.

This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resource-distributing (economical) sociotechnological systems (STS). This framework is meant to enable smart operation not only in a "e;business-as-usual"e; mode, but also in extraordinary, highly volatile or hazardous environments. It is the result of convergence and deep integration into a unified, flexible and effectively implemented formalism operating on multisets of several well-known paradigms from classical operations research and modern knowledge engineering, such as: mathematical programming, game theory, optimal scheduling, logic programming and constraint programming. The mathematical background needed for MGF, its algorithmics, applications, implementation issues, as well as its nexus with known models from operations research and theoretical computer science areas are considered. The resilience and recovery issues of an STS are studied by applying the MGF toolkit and on paying special attention to the multigrammatical assessment of resilience of energy infrastructures. MGF-represented resource-based games are introduced, and directions for further development are discussed. The author presents multiple applications to business intelligence, critical infrastructure, ecology, economy and industry. This book is addressed to scholars working in the areas of theoretical and applied computer science, artificial intelligence, systems analysis, operations research, mathematical economy and critical infrastructure protection, to engineers developing software-intensive solutions for implementation of the knowledge-based digital economy and Industry 4.0, as well as to students, aspirants and university staff. Foundational knowledge of set theory, mathematical logic and routine operations on data bases is needed to read this book. The content of the monograph is gradually presented, from simple to complex, in a well-understandable step-by-step manner. Multiple examples and accompanying figures are included in order to support the explanation of the various notions, expressions and algorithms.

This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates MESP in information theory, as the algorithmic problem of calculating a sub-vector of pre-specificed size from a multivariate Gaussian random vector, so as to maximize Shannon's differential entropy. The text collects and expands on state-of-the-art algorithms for MESP, and addresses its application in the field of environmental monitoring. While MESP is a central optimization problem in the theory of statistical designs (particularly in the area of spatial monitoring), this book largely focuses on the unique challenges of its algorithmic side. From the perspective of mathematical-optimization methodology, MESP is rather unique (a 0/1 nonlinear program having a nonseparable objective function), and the algorithmic techniques employed are highly non-standard. In particular, successful techniques come from several disparate areas within the field of mathematical optimization; for example: convex optimization and duality, semidefinite programming, Lagrangian relaxation, dynamic programming, approximation algorithms, 0/1 optimization (e.g., branch-and-bound), extended formulation, and many aspects of matrix theory. The book is mainly aimed at graduate students and researchers in mathematical optimization and data analytics. 

This work prepares current and future managers and consultants focused on health care delivery systems to improve the efficiency of processes that deliver care. This material will help you manage capacity, improve patient flow, estimate process costs, and conduct experiments that lead to process improvement. Essential tools covered include process mapping and measurement, data collection and analysis, and the use of discrete event simulation as a tool for virtual experimentation and improvement. Tools are introduced with no assumption of prior training. Many examples of settings, problems, and solutions are presented, along with a generalized approach to process improvement that is specifically tailored to health care settings. Readings, exercises, and cases suitable for discussion or end-course projects are also provided. Writing is based on a decade of experience teaching at the MBA and MS levels, managing dozens of improvement processes, and a host of our prior scholarly publications, book chapters, and case studies.