The papers presented in this open access book address diverse challenges in decarbonizing energy systems, ranging from operational to investment planning problems, from market economics to technical and environmental considerations, from distribution grids to transmission grids, and from theoretical considerations to data provision concerns and applied case studies. While most papers have a clear methodological focus, they address policy-relevant questions at the same time. The target audience therefore includes academics and experts in industry as well as policy makers, who are interested in state-of-the-art quantitative modelling of policy relevant problems in energy systems. The 2nd International Symposium on Energy System Optimization (ISESO 2018) was held at the Karlsruhe Institute of Technology (KIT) under the symposium theme "Bridging the Gap Between Mathematical Modelling and Policy Support" on October 10th and 11th 2018. ISESO 2018 was organized by the KIT, the Heidelberg Institute for Theoretical Studies (HITS), the Heidelberg University, the German Aerospace Center and the University of Stuttgart.

This book encompasses the study of hybrid switching di usion processes and their applications. The word \hybrid" signi es the coexistence of c- tinuous dynamics and discrete events, which is one of the distinct features of the processes under consideration. Much of the book is concerned with the interactions of the continuous dynamics and the discrete events. Our motivations for studying such processes originate from emerging and - isting applications in wireless communications, signal processing, queueing networks, production planning, biological systems, ecosystems, nancial engineering, and modeling, analysis, and control and optimization of lar- scale systems, under the in uence of random environments. Displaying mixture distributions, switching di usions may be described by the associated operators or by systems of stochastic di erential eq- tions together with the probability transition laws of the switching actions. We either have Markov-modulated switching di usions or processes with continuous state-dependent switching. The latter turns out to be much more challenging to deal with. Viewing the hybrid di usions as a number of di usions joined together by the switching process, they may be se- ingly not much di erent from their di usion counterpart. Nevertheless, the underlying problems become more di cult to handle, especially when the switching processes depend on continuous states. The di culty is due to the interaction of the discrete and continuous processes and the tangled and hybrid information pattern.

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.

"Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, "provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide. "

In this book, one of the most highly recognized entrepreneurship scholars shares in a personal and readable way his rich experience and ideas on how entrepreneurship can be researched. Entrepreneurship is a phenomenon of tremendous societal importance. It is also an elusive phenomenon, which makes researching it fun, fascinating-and frustrating at times. In this fully updated edition, numerous real examples accompany the treatment of problems and solutions concerning design, sampling, operationalization and analysis. Researching Entrepreneurship is targeted primarily at research students and academics who are relatively new to research or to entrepreneurship research. This said, basic knowledge of research methods is assumed, and when foundational issues are discussed they are typically approach from a non-standard angle and/or with an eye to illuminate entrepreneurship-specific problems and solutions. This makes large parts of the contents potentially valuable for entrepreneurship scholars at any level of research proficiency. The book is also of interest to sophisticated, non-academic users with a professional interest in collecting and analyzing data from emerging and young ventures, and to those who make use of published entrepreneurship research. For example, analysts in marketing research or consultancy firms, business associations, statistical agencies and other government offices may find this book to be a valuable tool. Moreover, while the examples are derived from entrepreneurship research, the book provides a unique "experienced empirical researcher" (rather than "textbook method expert") treatment of issues that are of equal relevance across the social sciences. This goes for topics like the role of theory; research design; validity assessment; statistical inference, and replication. Entrepreneurship research has developed rapidly in the decade that has passed since the first edition. Therefore, all chapters have been comprehensively updated and many have been extended; sometimes to twice the original length. Two of the original chapters have been excluded to make room for entirely new chapters on "the Dependent Variable" and "The Entrepreneurship Nexus." While retaining a unique, personal tone, the author uses examples and references that build on contributions from a large number of top entrepreneurship researchers.

The availability of today's online information systems rapidly increases the relevance of dynamic decision making within a large number of operational contexts. Whenever a sequence of interdependent decisions occurs, making a single decision raises the need for anticipation of its future impact on the entire decision process. Anticipatory support is needed for a broad variety of dynamic and stochastic decision problems from different operational contexts such as finance, energy management, manufacturing and transportation. Example problems include asset allocation, feed-in of electricity produced by wind power as well as scheduling and routing. All these problems entail a sequence of decisions contributing to an overall goal and taking place in the course of a certain period of time. Each of the decisions is derived by solution of an optimization problem. As a consequence a stochastic and dynamic decision problem resolves into a series of optimization problems to be formulated and solved by anticipation of the remaining decision process.

However, actually solving a dynamic decision problem by means of approximate dynamic programming still is a major scientific challenge. Most of the work done so far is devoted to problems allowing for formulation of the underlying optimization problems as linear programs. Problem domains like scheduling and routing, where linear programming typically does not produce a significant benefit for problem solving, have not been considered so far. Therefore, the industry demand for dynamic scheduling and routing is still predominantly satisfied by purely heuristic approaches to anticipatory decision making. Although this may work well for certain dynamic decision problems, these approaches lack transferability of findings to other, related problems.

This book has serves two major purposes:

It provides a comprehensive and unique view of anticipatory optimization for dynamic decision making. It fully integrates Markov decision processes, dynamic programming, data mining and optimization and introduces a new perspective on approximate dynamic programming. Moreover, the book identifies different degrees of anticipation, enabling an assessment of specific approaches to dynamic decision making.

It shows for the first time how to successfully solve a dynamic vehicle routing problem by approximate dynamic programming. It elaborates on every building block required for this kind of approach to dynamic vehicle routing. Thereby the book has a pioneering character and is intended to provide a footing for the dynamic vehicle routing community."

As time and distance become conquerable in a global economy, understanding the future of supply chain management is the process of understanding how the world interacts. Innovations in Logistics and Supply Chain Management Technologies for Dynamic Economies disseminates supply chain management and applied logistic theories, technology development, innovation, and transformation in various economic sectors upon current, advancing technological opportunities and market imperatives. In a world where efficiency is crucial, applied research and developments in logistics and supply chain management included in this volume is paramount.

This book proposes novel methods for solving different types of non-cooperative games with interval/fuzzy/intuitionistic fuzzy payoffs. It starts by discussing several existing methods and shows that some mathematically incorrect assumptions have been considered in all these methods. It then proposes solutions to adapt those methods and validate the new proposed methods, such as Gaurika method Ambika-I-IV, Mehar method and others, by using them for solving existing numerical problems. The book offers a comprehensive guide on non-cooperative games with fuzzy payoffs to both students and researchers. It provides them with the all the necessary tools to understand the methods and the theory behind them.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.