This book presents innovative operations research applications in business, specifically industrial engineering and its sub-disciplines. It investigates new perspectives in operations research and management science with regard to research methods, the research context, and industrial engineering, offering readers a broad range of new approaches to management problems. The book features the latest work of researchers who have worked with Professor Fusun Ulengin or built upon her work in their academic careers. Written in honor of Prof. Ulengin, this book was edited by her former Ph.D. students, who are now experts in operations research, multiple criteria decision making, competitiveness, logistics, and supply chain management. Prof. Ulengin’s impact in academia is visible in the range of topics and methodologies featured in this book: Location and transportation problems, competitiveness of nations, food supply chains, debt collection, mathematical modelling, multiple criteria decision making, data envelopment analysis, random forests, and Bayesian networks.
This book provides comprehensive coverage of the latest research on multiple criteria research analysis (MCDA) and related areas, gathering a collection of high-quality chapters prepared by leading scholars in the field. By covering the established streams in MCDA research and simultaneously exploring new and emerging areas of application, it offers a unique reference resource for the future development of MCDA. The book approaches MCDA as one of the most active areas in operations research and management science (OR/MS). It presents not only the significant advances achieved to date, but also the new opportunities and challenges arising for both the theory and practice of MCDA. Among many others, the book addresses behavioral and conceptual aspects of decision aiding and decision making, problem structuring issues in the framework of new technological and socio-economic advances, methodological and algorithmic advances for analytical modeling and decision aiding, as well as a number of new application areas in engineering, business, and the social sciences.
Within global commerce, services and management play a vital role in the economy. Service systems are necessary for organizations, and a multi-disciplinary approach is ideal to establish full understanding of these systems. Best Practices and New Perspectives in Service Science and Management provides original research on all aspects of service science, service management, service engineering, and its supporting technology in order to administer cutting-edge knowledge to encourage the improvement of services. This book is essential for researchers and practitioners in the fields of computer science, software management, and engineering.
Globalization and digitalization are buzz words in contemporary society. They affect both our private and our professional lives. Society has become more diverse with easier access to information and to virtual platforms that gives us opportunity to be in touch with colleagues, friends, family, etc. at any time. A complex environment is emerging wherein internet of things and big data are being integrated with products, production systems, healthcare, and daily activity and play an important part in decision making. This has an impact on future designs and the role of designers. Responsible designers with a holistic perspective are needed. The book highlights several aspects of design thinking such as Information Design and Critical Design. The meaning of culture, gender and disabilities are also discussed. The functions of Information Design are changing from ‘showing the way’, instruction manuals and graphic design. It will affect among others, healthcare technology, smart products and Industry 4.0. Design thinking perspective that includes users from the entire chain and from the producer to the end user of the product or service, is needed. This will also require gender and culture issues to be taken into consideration in designing products and services. Design thinking methods and critical aspects of design will contribute to an inclusive society.
This book describes various methods of analysis for ascertaining the effects of agglomeration economies, which are important for formulating regional economic policies. Specifically, it describes new analytical approaches using productivity and productive efficiency analyses as methods for understanding agglomeration economies. Additionally, the book provides application results for Japanese regions and proposes desirable regional policies. According to the new analytical methods advocated in this book, agglomeration economies are larger in major metropolitan areas than in local regions, and in the manufacturing sector than in the non-manufacturing sector. These results are consistent with general knowledge. Moreover, the majority of productivity growth pertaining to regional economies is explainable by improvements to accessibility. Improving accessibility for regions reduces transportation costs between them and strengthens agglomeration economies, which, in turn, enable the sustainable development of regional economies. Therefore, this book highlights the need not only to reinforce existing agglomeration areas, but also to form a network between these agglomerations and to strengthen it, so as to realize regional economic growth despite a decreasing population.
This Handbook is a collection of chapters on key issues in the design and analysis of computer simulation experiments on models of stochastic systems. The chapters are tightly focused and written by experts in each area. For the purpose of this volume “simulation refers to the analysis of stochastic processes through the generation of sample paths (realization) of the processes. Attention focuses on design and analysis issues and the goal of this volume is to survey the concepts, principles, tools and techniques that underlie the theory and practice of stochastic simulation design and analysis. Emphasis is placed on the ideas and methods that are likely to remain an intrinsic part of the foundation of the field for the foreseeable future. The chapters provide up-to-date references for both the simulation researcher and the advanced simulation user, but they do not constitute an introductory level ‘how to’ guide. Computer scientists, financial analysts, industrial engineers, management scientists, operations researchers and many other professionals use stochastic simulation to design, understand and improve communications, financial, manufacturing, logistics, and service systems. A theme that runs throughout these diverse applications is the need to evaluate system performance in the face of uncertainty, including uncertainty in user load, interest rates, demand for product, availability of goods, cost of transportation and equipment failures. * Tightly focused chapters written by experts * Surveys concepts, principles, tools, and techniques that underlie the theory and practice of stochastic simulation design and analysis * Provides an up-to-date reference for both simulation researchers and advanced simulation users
Operations Research (OR) began as an interdisciplinary activity to solve complex military problems during World War II. Utilizing principles from mathematics, engineering, business, computer science, economics, and statistics, OR has developed into a full fledged academic discipline with practical application in business, industry, government and military. Currently regarded as a body of established mathematical models and methods essential to solving complicated management issues, OR provides quantitative analysis of problems from which managers can make objective decisions. Operations Research and Management Science (OR/MS) methodologies continue to flourish in numerous decision making fields. Featuring a mix of international authors, Operations Research and Management Science Handbook combines OR/MS models, methods, and applications into one comprehensive, yet concise volume. The first resource to reach for when confronting OR/MS difficulties, this text – Provides a single source guide in OR/MS Bridges theory and practice Covers all topics relevant to OR/MS Offers a quick reference guide for students, researchers and practitioners Contains unified and up-to-date coverage designed and edited with non-experts in mind Discusses software availability for all OR/MS techniques Includes contributions from a mix of domestic and international experts The 26 chapters in the handbook are divided into two parts. Part I contains 14 chapters that cover the fundamental OR/MS models and methods. Each chapter gives an overview of a particular OR/MS model, its solution methods and illustrates successful applications. Part II of the handbook contains 11 chapters discussing the OR/MS applications in specific areas. They include airlines, e-commerce, energy systems, finance, military, production systems, project management, quality control, reliability, supply chain management and water resources. Part II ends with a chapter on the future of OR/MS applications.
This book presents recent research in intelligent and fuzzy techniques on digital transformation and the new normal, the state to which economies, societies, etc. settle following a crisis bringing us to a new environment. Digital transformation and the new normal-appearing in many areas such as digital economy, digital finance, digital government, digital health, and digital education are the main scope of this book. The readers can benefit from this book for preparing for a digital “new normal” and maintaining a leadership position among competitors in both manufacturing and service companies. Digitizing an industrial company is a challenging process, which involves rethinking established structures, processes, and steering mechanisms presented in this book. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying digital transformation and new normal. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.
From the Foreword by Marshall Fisher, The Wharton School, University of Pennsylvania: As generation of academics and practitioners follows generation, it is worthwhile to compile long views of the research and practice in the past to shed light on research and practice going forward. This collection of peer-reviewed articles is intended to provide such a long view. This book contains a collection of chapters written by leading scholars/practitioners who have continued their efforts in developing and/or implementing innovative OR/MS tools for solving real world problems. In this book, the contributors share their perspectives about the past, present and future of OR/MS theoretical development, solution tools, modeling approaches, and applications. Specifically, this book collects chapters that offer insights about the following topics: • Survey articles taking a long view over the past two or more decades to arrive at the present state of the art while outlining ideas for future research. Surveys focus on use of a particular OR/MS approach, e.g., mathematical programming (LP, MILP, etc.) and solution methods for particular family of application, e.g., distribution system design, distribution planning system, health care. • Autobiographical or biographical accounts of how particular inventions (e.g., Structured Modeling) were made. These could include personal experiences in early development of OR/MS and an overview of what has happened since. • Development of OR/MS mathematical tools (e.g., stochastic programming, optimization theory). • Development of OR/MS in a particular industry sector such as global supply chain management. • Modeling systems for OR/MS and their development over time as well as speculation on future development (e.g., LINDO, LINGO, and What’sBest!) • New applications of OR/MS models (e.g., happiness) The target audience of this book is young researchers, graduate/advanced undergraduate students from OR/MS and related fields like computer science, engineering, and management as well as practitioners who want to understand how OR/MS modeling came about over the past few decades and what research topics or modeling approaches they could pursue in research or application.
Operations Research: 1934-1941," 35, 1, 143-152; "British The goal of the Encyclopedia of Operations Research and Operational Research in World War II," 35, 3, 453-470; Management Science is to provide to decision makers and "U. S. Operations Research in World War II," 35, 6, 910-925; problem solvers in business, industry, government and and the 1984 article by Harold Lardner that appeared in academia a comprehensive overview of the wide range of Operations Research: "The Origin of Operational Research," ideas, methodologies, and synergistic forces that combine to 32, 2, 465-475. form the preeminent decision-aiding fields of operations re search and management science (OR/MS). To this end, we The Encyclopedia contains no entries that define the fields enlisted a distinguished international group of academics of operations research and management science. OR and MS and practitioners to contribute articles on subjects for are often equated to one another. If one defines them by the which they are renowned. methodologies they employ, the equation would probably The editors, working with the Encyclopedia's Editorial stand inspection. If one defines them by their historical Advisory Board, surveyed and divided OR/MS into specific developments and the classes of problems they encompass, topics that collectively encompass the foundations, applica the equation becomes fuzzy. The formalism OR grew out of tions, and emerging elements of this ever-changing field. We the operational problems of the British and U. s. military also wanted to establish the close associations that OR/MS efforts in World War II.
The chapters of this Handbook volume cover nine main topics that are representative of recent theoretical and algorithmic developments in the field. In addition to the nine papers that present the state of the art, there is an article on the early history of the field. The handbook will be a useful reference to experts in the field as well as students and others who want to learn about discrete optimization.
Design Models for Hierarchical Organizations: Computation, Information, and Decentralization provides state-of-the-art research on organizational design models, and in particular on mathematical models. Each chapter views the organization as an information processing entity. Thus, mathematical models are used to examine information flow and decision procedures, which in turn, form the basis for evaluating organization designs. Each chapters stands alone as a contribution to organization design and the modeling approach to design. Moreover, the chapters fit together and that totality gives us a good understanding of where we are with this approach to organizational design issues and where we should focus our research efforts in the future.