The chapters in this volume explore how various methods from game theory can be utilized to optimize security and risk-management strategies. Emphasizing the importance of connecting theory and practice, they detail the steps involved in selecting, adapting, and analyzing game-theoretic models in security engineering and provide case studies of successful implementations in different application domains. Practitioners who are not experts in game theory and are uncertain about incorporating it into their work will benefit from this resource, as well as researchers in applied mathematics and computer science interested in current developments and future directions. The first part of the book presents the theoretical basics, covering various different game-theoretic models related to and suitable for security engineering. The second part then shows how these models are adopted, implemented, and analyzed. Surveillance systems, interconnected networks, and power grids are among the different application areas discussed. Finally, in the third part, case studies from business and industry of successful applications of game-theoretic models are presented, and the range of applications discussed is expanded to include such areas as cloud computing, Internet of Things, and water utility networks.

Metaheuristics exhibit desirable properties like simplicity, easy parallelizability, and ready applicability to different types of optimization problems. After a comprehensive introduction to the field, the contributed chapters in this book include explanations of the main metaheuristics techniques, including simulated annealing, tabu search, evolutionary algorithms, artificial ants, and particle swarms, followed by chapters that demonstrate their applications to problems such as multiobjective optimization, logistics, vehicle routing, and air traffic management. The authors are leading researchers in this domain, with considerable teaching and applications experience, and the book will be of value to industrial practitioners, graduate students, and research academics.

Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.

This book offers an in-depth and comprehensive introduction to the priority methods of intuitionistic preference relations, the consistency and consensus improving procedures for intuitionistic preference relations, the approaches to group decision making based on intuitionistic preference relations, the approaches and models for interactive decision making with intuitionistic fuzzy information, and the extended results in interval-valued intuitionistic fuzzy environments.

This handbook is a compilation of comprehensive reference sources that provide state-of-the-art findings on both theoretical and applied research on sustainable fashion supply chain management. It contains three parts, organized under the headings of "Reviews and Discussions," "Analytical Research," and "Empirical Research," featuring peer-reviewed papers contributed by researchers from Asia, Europe, and the US. This book is the first to focus on sustainable supply chain management in the fashion industry and is therefore a pioneering text on this topic. In the fashion industry, disposable fashion under the fast fashion concept has become a trend. In this trend, fashion supply chains must be highly responsive to market changes and able to produce fashion products in very small quantities to satisfy changing consumer needs. As a result, new styles will appear in the market within a very short time and fashion brands such as Zara can reduce the whole process cycle from conceptual design to a final ready-to-sell "well-produced and packaged" product on the retail sales floor within a few weeks. From the supply chain's perspective, the fast fashion concept helps to match supply and demand and lowers inventory. Moreover, since many fast fashion companies, e.g., Zara, H&M, and Topshop, adopt a local sourcing approach and obtain supply from local manufacturers (to cut lead time), the corresponding carbon footprint is much reduced. Thus, this local sourcing scheme under fast fashion would enhance the level of environmental friendliness compared with the more traditional offshore sourcing. Furthermore, since the fashion supply chain is notorious for generating high volumes of pollutants, involving hazardous materials in the production processes, and producing products by companies with low social responsibility, new management principles and theories, especially those that take into account consumer behaviours and preferences, need to be developed to address many of these issues in order to achieve the goal of sustainable fashion supply chain management. The topics covered include Reverse Logistics of US Carpet Recycling; Green Brand Strategies in the Fashion Industry; Impacts of Social Media on Consumers' Disposals of Apparel; Fashion Supply Chain Network Competition with Eco-labelling; Reverse Logistics as a Sustainable Supply Chain Practice for the Fashion Industry; Apparel Manufacturers' Path to World-class Corporate Social Responsibility; Sustainable Supply Chain Management in the Slow-Fashion Industry; Mass Market Second-hand Clothing Retail Operations in Hong Kong; Constraints and Drivers of Growth in the Ethical Fashion Sector: The case of France; and Effects of Used Garment Collection Programmes in Fast Fashion Brands.

Knowledge capital is at the core of the socio-economic global system. Profit and not-for profit firms, institutions, and organizations, in general, face unique opportunities and threats related to knowledge management. Digital technologies and digital transformation offer a wide array of opportunities for value creation. At the same time, organizations need to foster newer, faster, and more dynamic ways of mobilizing and managing knowledge. Emerging trends, such as artificial intelligence, collective intelligence, agile methodologies, open innovation, and co-creation enable new business models and managerial paradigms that need to be understood and conceptualized. This book offers an extensive overview of the most recent trends in knowledge management and the most advanced theoretical approaches, while, at the same time, providing a wide array of case studies and evidence-based knowledge management practices. It takes into account the interrelation between ICT and knowledge management challenges, in terms of human/non-human interactions, which requires extraordinary organizational change and renewal. Further, the book presents an up-to-date examination of and guidance for the implementation of knowledge management in an era of unprecedented human/non-human interaction. The book conveys the results of more than a decade of research and applied experience in the field of knowledge management carried out by the author. It is intended not only for students and academics but also for managers and practitioners who are interested in deepening their understanding of knowledge and learning.

This book studies the urban logistics system from the perspective of reliability, based on the theory of urban logistics and system reliability, with the research of urban logistics system reliability as the main line, with matter element analysis and ant colony algorithm as the main research tools. On this basis, this book closely focuses on the connotation, influencing factors, measurement, optimization, and other issues of the reliability of urban logistics systems. By analyzing the influencing factors and constituent contents of the reliability of urban logistics system, the reliability measurement is researched, and the reliability optimization model of urban logistics system is established, which is suitable for popular science reading or in-depth study by readers with a certain foundation.

Exploring the three levels of project management, this edited collection analyses the practice of problem structuring approaches (PSAs) with an aim to improve organisational adaptability and value creation. By studying these approaches, the authors present techniques for enhancing project management knowledge, informing decision-making and guiding management actions. This book is an insightful and timely read, as it addresses the need for organisations to adapt in order to tackle new challenges within today's changing business landscape. Undoubtedly useful to those studying project management and operational research, this book is also an important read for managers and decision-makers within organisations as it identifies and examines the effective outcomes of PSAs.

Business Intelligence (BI) is a solution to modern business problems. This book discusses the relationship between BI and Human Resource Management (HRM). In addition, it discusses how BI can be used as a strategic decision-making tool for the sustainable growth of an organization or business. BI helps organizations generate interactive reports with clear and reliable data for making numerous business decisions. This book covers topics spanning the important areas of BI in the context of HRM. It gives an overview of the aspects, tools, and techniques of BI and how it can assist HRM in creating a successful future for organizations. Some of the tools and techniques discussed in the book are analysis, data preparation, BI-testing, implementation, and optimization on GR and management disciplines. It will include a chapter on text mining as well as a section of case studies for practical use. This book will be useful for business professionals, including but not limited to, HR professionals, and budding business students.

This book deals with the choice of methods to be applied in the decision processes within organizations. It discusses the use of voting procedures for group decision in business organizations, focusing on decision-making contexts. Within this book the reader explores the relevant part of the decision-making process consisting of choosing the voting procedures and recognizing the drawbacks of that procedure. This book includes a unique feature of providing a framework for choosing the voting procedure that is the most appropriate for a particular business decision process. The book is useful for a broad researcher audience dealing with the group decision making processes within business organizations and for practitioners and students working in the group decision and negotiation field.

This book gathers a selection of refereed papers presented at the 4th International Symposium and 26th National Conference of the Hellenic Operational Research Society. It highlights recent scientific advances in operational research and management science (OR/MS), with a focus on linking OR/MS with other areas of quantitative methods in a multidisciplinary framework. Topics covered include areas such as business process modeling, supply chain management, organization performance and strategy planning, revenue management, financial applications, production planning, metaheuristics, logistics, inventory systems, and energy systems.

Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book. Recent advances in information technology have transformed the use of resources and data exchange, often leading to management and optimization problems attributatble to technology limitations and strong market competition. This book discusses several problems and concepts which makes significant connections in the areas of information sharing, organization management, resource operations, and performance assessment. Geared toward practitioners and researchers, this treatment deepens the understanding between resource collaborative management and advanced information technology. Those in manufacturing will utilize the numerous mathematical models and methods offered to solve practical problems related to cutting stock, supply chain scheduling, and inventory management. Academics and students with a basic knowledge of manufacturing, combinatorics, and linear programming will find that this discussion widens the research area of resource collaborative management and unites the fields of information technology, manufacturing management, and optimization.

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques - especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: * Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) * Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics * An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata * A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters - Static Simulation Optimization, Reinforcement Learning and Convergence Analysis - this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

Includes a balanced coverage of modeling as well as applications of layout, materials handling, and warehousing Presents automated materials handling and warehousing along with queuing, queuing network, and basic simulation modeling Introduces new material on supply chain designing and management, aggregate planning and stochastic inventory control, transportation, and logistics/distribution Provides Layout-iQ software and data files from the authors own website Offers a solutions manual and PowerPoint slides for qualified textbook adoption

Multiple Criteria Decision Making (MCDM) is the study of methods and procedures by which concerns about multiple conflicting criteria can be formally incorporated into the management planning process. A key area of research in OR/MS, MCDM is now being applied in many new areas, including GIS systems, AI, and group decision making. Additionally, there has been very rapid growth in recent years in evolutionary Multiobjective optimization, stochastic analysis, robustness, and regression-based methods, and thus, the need for a look at the newest trends in the field.

This volume is in effect the third book in the Springer ISOR series by these editors, bringing the latest developments in MCDM into focus. It presents research from leaders in the field on such topics as Problem Structuring Methodologies; Measurement Theory and MCDA; Recent Developments in Evolutionary Multiobjective Optimization; Habitual Domains and Dynamic MCDM in Changeable Spaces; Stochastic Multicriteria Acceptability Analysis; and more.

Manufacturing companies need to adapt to the requirements of functioning in the era of Industry 4.0 and major technological disruptions. The use of knowledge-based decision support tools has also become necessary in order for enterprises to survive in a competitive environment. This book offers a new approach to designing the knowledge management process and integrating it with the implementation of Industry 4.0 technology. The book presents the methods used in a customer-oriented organisation for management of manufacturing knowledge. More specifically, methods for defining and collecting customer requirements are presented and methods on how to receive manufacturing knowledge, as well as how to formalise the acquired knowledge using key technologies of Industry 4.0, are discussed. The author also presents real case studies from Western and Central Europe and offers recommendations for the production manager. The instrumentation of methods and tools to support knowledge management, in the production of individualised products presented therein, will allow the manufacturing company to be transformed digitally into a customer-oriented organisation operating in accordance with the assumptions of Industry 4.0. This book will be a valuable read for production researchers, academicians, PhD students and postgraduate-level students of industrial engineering and industrial management. The practical case studies will also make the book a useful resource for managers of manufacturing enterprises.

The book offers a comprehensive and timely overview of advanced mathematical tools for both uncertainty analysis and modeling of parallel processes, with a special emphasis on intuitionistic fuzzy sets and generalized nets. The different chapters, written by active researchers in their respective areas, are structured to provide a coherent picture of this interdisciplinary yet still evolving field of science. They describe key tools and give practical insights into and research perspectives on the use of Atanassov's intuitionistic fuzzy sets and logic, and generalized nets for describing and dealing with uncertainty in different areas of science, technology and business, in a single, to date unique book. Here, readers find theoretical chapters, dealing with intuitionistic fuzzy operators, membership functions and algorithms, among other topics, as well as application-oriented chapters, reporting on the implementation of methods and relevant case studies in management science, the IT industry, medicine and/or education. With this book, the editors wish to pay homage to Professor Krassimir Todorov Atanassov for his pioneering work on both generalized nets and intuitionistic fuzzy set.

The figure of the entrepreneur has become a relevant factor that explains the process of growth and economic development. Rising unemployment rates have generated among institutional and private agents, a significant interest in promoting entrepreneurship as a formula to eradicate this social scourge of unemployment. Active policies that favor business culture and initiative are being promoted in all areas. In the university world, academic research has multiplied the work on entrepreneurship, a term that includes a triple meaning: the figure of the entrepreneur, the business function and the creation of companies. This versatile meaning must be based on a consistent theory about the company and the entrepreneur. This book presents specific cases of companies and entrepreneurs that have had their role throughout the history of Spain. The intention is to show the techniques and learning acquired by those agents, which have allowed a considerable advance in the knowledge of the structure and business development. This book brings together the research carried out by its authors with primary sources and makes it accessible to a wide audience-Spanish and Latin American-and will be of value to researchers, academics, and students with an interest in Spanish entrepreneurship, business, and management history.

This book describes Python3 programming resources for implementing decision aiding algorithms in the context of a bipolar-valued outranking approach. These computing resources, made available under the name Digraph3, are useful in the field of Algorithmic Decision Theory and more specifically in outranking-based Multiple-Criteria Decision Aiding (MCDA). The first part of the book presents a set of tutorials introducing the Digraph3 collection of Python3 modules and its main objects, such as bipolar-valued digraphs and outranking digraphs. In eight methodological chapters, the second part illustrates multiple-criteria evaluation models and decision algorithms. These chapters are largely problem-oriented and demonstrate how to edit a new multiple-criteria performance tableau, how to build a best choice recommendation, how to compute the winner of an election and how to make rankings or ratings using incommensurable criteria. The book's third part presents three real-world decision case studies, while the fourth part addresses more advanced topics, such as computing ordinal correlations between bipolar-valued outranking digraphs, computing kernels in bipolar-valued digraphs, testing for confidence or stability of outranking statements when facing uncertain or solely ordinal criteria significance weights, and tempering plurality tyranny effects in social choice problems. The fifth and last part is more specifically focused on working with undirected graphs, tree graphs and forests. The closing chapter explores comparability, split, interval and permutation graphs. The book is primarily intended for graduate students in management sciences, computational statistics and operations research. The chapters presenting algorithms for ranking multicriteria performance records will be of computational interest for designers of web recommender systems. Similarly, the relative and absolute quantile-rating algorithms, discussed and illustrated in several chapters, will be of practical interest to public and private performance auditors.

Open internationalization is a concept that brings a new perspective on the process of firm internationalization. As theories of internationalization show, some companies expand abroad only on their own, known as closed internationalization, while others combine their resources with those of other firms or use their networks for facilitating foreign implantation, known as open internationalization. Parallel to the development of the well-known concept of open innovation, open internationalization can be conceived as a meta-model for understanding companies' expansion abroad. This book gathers a selection of contemporary research works dedicated to open internationalization, either seen as a way to analyze expansion in foreign countries, or as a way to investigate the management of geographically dispersed activities. All the authors of the chapters are researchers specialized in the internationalization field. Readers will benefit from this new lens for understanding, studying or practising international business, from the decision to go abroad to its implementation and its efficiency. Open Internationalization Strategy includes both academic empirical investigations and literature reviews on specific topics, making it valuable to researchers, academics, managers, and students in the fields of business and management history, international business, organizational studies, and economics.

Consumer co-operatives provide a different approach to organizing business through their ideals of member ownership and democratic practice. Every co-operative member has an equal vote regardless of his or her own personal capital investment. The co-operative movement can also be an important force in promoting development and self-sufficiency in poorer areas, particularly in non-industrialised countries. This book explores in depth the fortunes of the Berkeley Consumer Co-operative, which became the largest consumer co-operative in the United States with 116,000 members in 1984 and viewed nationally as a leader in innovative retail practices and a champion of consumer rights. The Berkeley Consumer Co-operative is promoted by both supporters and opponents of the co-operative business model as a significant example of what can go wrong with the co-operatives. This book will provide the first in depth analysis of the history of the Berkeley Co-operative using its substantial but little used archives and oral histories to explore what the Berkeley experience means for the co-operative business model. The specific chapters relating to Berkeley will be organised around particular themes to highlight the issues relating to the co-operative business model and the local context of Berkeley. The themes relate to developments in Berkeley and the Bay Area in terms of the economy, politics and the retail environment; the management of the Berkeley co-operative, looking at governance, financial management and strategic decisions; relationship of management with members and employees; and finally, the relationship of the Berkeley Co-operative with the community. The core message of the book is that it is not inevitable that consumer co-operatives fail, but that the story of Berkeley story can provide insights that can strengthen the co-operative business model and minimise failures on the scale of Berkeley occurring in the future.

This book presents methods for full-wave computer simulation that can be used in various applications and contexts, e.g. seismic prospecting, earthquake stability, global seismic patterns on Earth and Mars, medicine, traumatology, ultrasound investigation of the human body, ultrasound and laser operations, ultrasonic non-destructive railway testing, modelling aircraft composites, modelling composite material delamination, etc. The key innovation of this approach is the ability to study spatial dynamical wave processes, which is made possible by cutting-edge numerical finite-difference grid-characteristic methods. The book will benefit all students, researchers, practitioners and professors interested in numerical mathematics, computer science, computer simulation, high-performance computer systems, unstructured meshes, interpolation, seismic prospecting, geophysics, medicine, non-destructive testing and composite materials.

The thesis provides different opportunities and ideas to face some current challenges in the electricity systems. It focuses on the effective and efficient integration of distributed low carbon technologies in the grid of the future. Planning and operation problems for different clean solutions, such as market bidding strategies for intermittent energy producers, demand side management algorithms for smart buildings, and electrical storage options for network operators, are studied for facilitating the integration of renewable energy sources in the power system chain.

The subject for this book is my life work on the enterprise modeling and integration by a stochastic/queuing form, and the book plan was conceived before my stay in the USA in 1996-97 as a visiting scholar. The rst title was "Stochastic Management and Design of Manufacturing Systems." The rst version was attempted in 2001; however, this version was inappropriate and was not revised till now. It is 40 years since I attempted a stochastic approach to manufacturing and management due to the limitations of statistical approaches. The century in which industrial engineering and management rose to the forefront was one in which a static/statistical approach was applied to the development of classical models and general/average theory. This book presents a stochastic management approach to the manufacturing and service enterprise with risks by a game/strategic view, and is based on many papers in production/queueing studies that have appeared in famous journals. The book's objective is to discuss and show the goals and constraints on manufacturing and service enterprises, and to provide a strategic/collaborative solution for management with risks in heterogeneity. This book mainly focuses on the three manufacturing classes: continuous, poi- wise, and exible stream types under risks. These manufacturing streams are rst studied using the respective stochastic processes, and are characterized and dev- oped as a queueing/strategic control problem of look-ahead/buffer, selection/swit- over, and arrangement/routings. Moreover, the behaviors of some design/control variables are shown and useful theories for design are established.

This volume contains contributions from prominent researchers who participated in the 2007 IAENG International Conference on Operations Research. Topics covered include quality management systems, reliability and quality control, engineering experimental design, computer supported collaborative engineering, human factors and ergonomics, computer aided manufacturing, manufacturing processes and methods, engineering management and leadership, optimization, transportation network design, stochastics modelling, queueing theory, and industrial applications. The book offers the states of arts of tremendous advances in communication systems and electrical engineering and also serve as an excellent reference work for researchers and graduate students working with/on industrial engineering and operations research.