This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments. No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains.

This open access book analyzes and seeks to consolidate the use of robust quantitative tools and qualitative methods for the design and assessment of energy and climate policies. In particular, it examines energy and climate policy performance and associated risks, as well as public acceptance and portfolio analysis in climate policy, and presents methods for evaluating the costs and benefits of flexible policy implementation as well as new framings for business and market actors. In turn, it discusses the development of alternative policy pathways and the identification of optimal switching points, drawing on concrete examples to do so. Lastly, it discusses climate change mitigation policies' implications for the agricultural, food, building, transportation, service and manufacturing sectors.

Interest in the phenomenon known as "lean" has grown significantly in recent years. This is the first volume to provide an academically rigorous overview of the field of lean management, introducing the reader to the application of lean in diverse application areas, from the production floor to sales and marketing, from the automobile industry to academic institutions. The volume collects contributions from well-known lean experts and up-and-coming scholars from around the world. The chapters provide a detailed description of lean management across the manufacturing enterprise (supply chain, accounting, production, sales, IT etc.), and offer important perspectives for applying lean across different industries (construction, healthcare, logistics). The contributors address challenges and opportunities for future development in each of the lean application areas, concluding most chapters with a short case study to illustrate current best practice. The book is divided into three parts: The Lean Enterprise Lean across Industries A Lean World. This handbook is an excellent resource for business and management students as well as any academics, scholars, practitioners, and consultants interested in the "lean world."

This book presents a range of qualitative and quantitative analyses in areas such as cybersecurity, sustainability, multivariate analysis, customer satisfaction, parametric programming, software reliability growth modeling, and blockchain technology, to name but a few. It also highlights integrated methods and practices in the areas of machine learning and genetic algorithms. After discussing applications in supply chains and logistics, cloud computing, six sigma, production management, big data analysis, satellite imaging, game theory, biometric systems, quality, and system performance, the book examines the latest developments and breakthroughs in the field of science and technology, and provides novel problem-solving methods. The themes discussed in the book link contributions by researchers and practitioners from different branches of engineering and management, and hailing from around the globe. These contributions provide scholars with a platform to derive maximum utility in the area of analytics by subscribing to the idea of managing business through system sciences, operations, and management. Managers and decision-makers can learn a great deal from the respective chapters, which will help them devise their own business strategies and find real-world solutions to complex industrial problems.

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.

This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach. The book is divided into six parts. Part 1 is devoted to the state-of-the-art theoretical foundation of MDP, including approximate methods such as policy improvement, successive approximation and infinite state spaces as well as an instructive chapter on Approximate Dynamic Programming. It then continues with five parts of specific and non-exhaustive application areas. Part 2 covers MDP healthcare applications, which includes different screening procedures, appointment scheduling, ambulance scheduling and blood management. Part 3 explores MDP modeling within transportation. This ranges from public to private transportation, from airports and traffic lights to car parking or charging your electric car . Part 4 contains three chapters that illustrates the structure of approximate policies for production or manufacturing structures. In Part 5, communications is highlighted as an important application area for MDP. It includes Gittins indices, down-to-earth call centers and wireless sensor networks. Finally Part 6 is dedicated to financial modeling, offering an instructive review to account for financial portfolios and derivatives under proportional transactional costs. The MDP applications in this book illustrate a variety of both standard and non-standard aspects of MDP modeling and its practical use. This book should appeal to readers for practitioning, academic research and educational purposes, with a background in, among others, operations research, mathematics, computer science, and industrial engineering.

This book is intended to present the milestones in the progression of uncertain Data envelopment analysis (DEA). Chapter 1 gives some basic introduction to uncertain theories, including probability theory, credibility theory, uncertainty theory and chance theory. Chapter 2 presents a comprehensive review and discussion of basic DEA models. The stochastic DEA is introduced in Chapter 3, in which the inputs and outputs are assumed to be random variables. To obtain the probability distribution of a random variable, a lot of samples are needed to apply the statistics inference approach. Chapter 4 and 5 provide two uncertain DEA methods to evaluate the DMUs with limited or insufficient statistical data, named fuzzy DEA and uncertain DEA. In order to evaluate the DMUs in which uncertainty and randomness appear simultaneously, the hybrid DEA based on chance theory is presented in Chapter 6.

This book provides readers with an introduction to m-polar fuzzy graphs and m-polar fuzzy hypergraphs, covering both theories and applications. A special emphasis is given to m-polar fuzzy graphs at the aim of filling a gap in the literature, namely the absence of a mathematical approach to analyze multi-index, multipolar, and multi-attribute data. The book describes metrics and labeling in m-polar graphs, m-polar fuzzy matroids. It also discusses in detail important applications in decision-making problems and imaging processing. The book is expected to stimulate the curiosity of mathematics, computer scientists, and social scientists alike, and to provide both students and researchers with the necessary knowledge to understand and apply m polar fuzzy graph theory.

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.

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 presents the construction and resolution of 50 practical optimization problems and covers an exceptionally wide range, including games-associated problems (Unblock Me, Sudokus), logistical problems, and problems concerning plant distribution, production, operations scheduling, management and resource allocation. The problems are divided into 5 difficulty levels. Problems in the first few levels are focused on learning the model construction methodology, while those in the last level include complex optimization environments. For each problem solution, the specific steps are illustrated, promoting reader comprehension. In addition, all the models are implemented in an optimization library, LINGO, their solutions have been analyzed and their correct construction has been verified. The book also includes a simple guide to implementing models in LINGO in a straightforward manner and in any input data format (text files, spreadsheets or databases). As an ideal companion to the author's previously published work Modelling in Mathematical Programming, the book is intended as a basic tool for students of operations research, and for researchers in any advanced area involving mathematical programming.

The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors' latest research, as well as on others' research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book represents a valuable reference guide for graduate students and researchers in the both fields of fuzzy logic and decision making.

This book bridges the fields of Supply Chain Management, Digital Transformation, and Dynamic Quality models in order to illustrate how digital transformation affects the work of researchers and managers in Supply Chain Quality problems. It aims to address the gap in scholarship regarding new technologies, updating the established literature to reimagine theoretical models, dynamic games, knowledge management, supply chain coordination solutions, interfaces in circular economies, and other functional spaces for a digital era. Written for researchers, managers, and practitioners, this book offers an accessible approach to the topics through clear, management-oriented chapters, reserving mathematical background for the Appendices. It discusses an array of modern challenges in digitization, including smart device installation, Cloud data accessibility, applications of AI systems, Supply Chain monitoring via Blockchains, using sensors in operations, and digital tool integration within traditional IS frameworks.

This research-oriented book presents key contributions on architecting the digital transformation. It includes the following main sections covering 20 chapters: * Digital Transformation * Digital Business * Digital Architecture * Decision Support * Digital Applications Focusing on digital architectures for smart digital products and services, it is a valuable resource for researchers, doctoral students, postgraduates, graduates, undergraduates, academics and practitioners interested in digital transformation.

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 presents the proceedings of the Seventh International Conference on Management Science and Engineering Management (ICMSEM2013) held from November 7 to 9, 2013 at Drexel University, Philadelphia, Pennsylvania, USA and organized by the International Society of Management Science and Engineering Management, Sichuan University (Chengdu, China) and Drexel University (Philadelphia, Pennsylvania, USA). The goals of the Conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current research findings. The selected papers cover various areas in management science and engineering management, such as Decision Support Systems, Multi-Objective Decisions, Uncertain Decisions, Computational Mathematics, Information Systems, Logistics and Supply Chain Management, Relationship Management, Scheduling and Control, Data Warehousing and Data Mining, Electronic Commerce, Neural Networks, Stochastic Models and Simulation, Fuzzy Programming, Heuristics Algorithms, Risk Control, Organizational Behavior, Green Supply Chains, and Carbon Credits. The proceedings introduce readers to novel ideas on and different problem-solving methods in Management Science and Engineering Management. We selected excellent papers from all over the world, integrating their expertise and ideas in order to improve research on Management Science and Engineering Management.

Very little has been published on optimization of pharmaceutical portfolios. Moreover, most of published literature is coming from the commercial side, where probability of technical success (PoS) is treated as fixed, and not as a consequence of development strategy or design. In this book there is a strong focus on impact of study design on PoS and ultimately on the value of portfolio. Design options that are discussed in different chapters are dose-selection strategies, adaptive design and enrichment. Some development strategies that are discussed are indication sequencing, optimal number of programs and optimal decision criteria. This book includes chapters written by authors with very broad backgrounds including financial, clinical, statistical, decision sciences, commercial and regulatory. Many authors have long held executive positions and have been involved with decision making at a product or at a portfolio level. As such, it is expected that this book will attract a very broad audience, including decision makers in pharmaceutical R&D, commercial and financial departments. The intended audience also includes portfolio planners and managers, statisticians, decision scientists and clinicians. Early chapters describe approaches to portfolio optimization from big Pharma and Venture Capital standpoints. They have stronger focus on finances and processes. Later chapters present selected statistical and decision analysis methods for optimizing drug development programs and portfolios. Some methodological chapters are technical; however, with a few exceptions they require a relatively basic knowledge of statistics by a reader.

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.

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

This new edition continues to emphasize the use of data envelopment analysis (DEA) to create optimization-based benchmarks within hospitals, physician group practices, health maintenance organizations, nursing homes and other health care delivery organizations. Suitable for graduate students learning DEA applications in health care as well as for practicing administrators, it is divided into two sections covering methods and applications. Section I considers efficiency evaluations using DEA; returns to scale; weight restricted (multiplier) models; non-oriented or slack-based models, including in this edition two versions of non-controllable variable models and categorical variable models; longitudinal (panel) evaluations and the effectiveness dimension of performance evaluation. A new chapter then looks at new and advanced models of DEA, including super-efficiency, congestion DEA, network DEA, and dynamic network models. Mathematical formulations of various DEA models are placed in end-of-chapter appendices. Section II then looks at health care applications within particular settings, chapter-by-chapter, including hospitals, physician practices, nursing homes and health maintenance organizations (HMOs). Other chapters then explore home health care and home health agencies; dialysis centers, community mental health centers, community-based your services, organ procurement organizations, aging agencies and dental providers; DEA models to evaluate provider performance for specific treatments, including stroke, mechanical ventilation and perioperative services. A new chapter then examines international-country-based applications of DEA in health care in 16 different countries, along with OECD and multi-country studies. Most of the existing chapters in this section were expanded with recent applications. Included with the book is online access to a learning version of DEA Solver software, written by Professor Kaoru Tone, which can solve up to 50 DMUs for various DEA models listed in the User's Guide at the end of the book.

This book provides an enduring response to modern economic problems and the consequent crises, dealing with the economic modelling of nations and the forecasting of economic growth. The main arguments embodied constitute the creation of jobs and the restoration of economic growth, using the implicit acceptance of analysis on differential models and neutral systems for controlling the wealth of nations.

This book addresses the current development status of high-speed railways globally and analyzes their operational schemes and practices under emergent conditions. It covers methods and problem-solving philosophy with regard to complexity analysis, capacity evaluation, passenger-flow forecasts, operating strategies, passenger-flow allocation, resource allocation and supporting technologies in the context of serious accidents and adverse environmental influences on train operation and service organization of high-speed railways. The abnormal scenarios, emergent conditions, adverse events and corresponding theoretical and applicational solutions dealing with the train operation both in line and network scale are all from real-world cases related to and designed for Chinese high-speed railway network which is the largest in scale, the highest in complexity and the most difficult in tackling with the complex and diverse climate and geographical environment , and thus makes the book both theoretically rigorous and practically applicable. It not only helps readers consider the train and network interactions from the perspective of complexity science, but also provides them with a philosophical framework and approaches available to construct their own roadmap and problem-solving paradigms in their daily research or management. This book is suitable for researchers, postgraduates and managerial and engineering practitioners in railway-related fields, especially in high-speed railway operation and emergency management.

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 is the first book to offer a complete spectrum of the role that operations research has played and can play in the improvement of North American freight railroads. It explores how decisions are made at railroads, contains examples of the mathematical programming formulations to the complex problems, and provides insights into real-world applications. The handbook is divided into eleven chapters, covering topics including scheduling problems, empty railcar distribution, and intermodal rail. These topics have been specifically selected to offer a thorough examination of the application of operations research at freight railroads. The chapters are written by recognized award-winning scholars and practitioners with a deep knowledge and understanding of their specific topics. The Handbook of Operations Research Applications at Railroads is an ideal resource for academics, experienced researchers, and consultants in the field.

This work is devoted to the late Ukrainian computer scientist V. M. Glushkov on the 90th anniversary of his birthday. Dr. Glushkov is known for his contribution to the world computer science and technology and this volume analyzes the ideas and paths of development of informatics formulated by him and demonstrate their important role in constructing computer technologies of basic research in the fields of applied mathematics, theories of computer programming and computing systems. A significant portion of the monograph is devoted to the elucidation of new results obtained in the field of mathematical modeling of complicated processes, creation of new methods for solving and investigating optimization problems in different statements and development of computer technologies for investigations in the field of economy, biology, medicine and information security in systems. The monograph will be of particular interest to informatics specialists and experts using methods of informatics and computer technologies to investigate complicated processes of different natures and developing new information technologies. It may also be useful for both graduate students and postgraduates specializing in Computer Science.