This book highlights what it takes to be successful in identifying and executing environmental responsibility from an operational perspective. It provides cutting-edge research from globally recognized field experts. It is a useful resource for practitioners to explore why and how firms engage in environmentally responsible operations, but also a valuable resource for academics as an introductory reference that provides direct exposure to key environmental operational problems faced by many firms today. This book can also be used as an introductory reading for students with varying educational backgrounds - from business school students interested in environmental issues to environmental scientists interested in obtaining a business perspective - as it provides a broad scope of key issues at the interface of operations management and environmental and social responsibility. Environmentally Responsible Supply Chains is structured in a modular fashion, with each chapter introducing and analyzing a specific timely topic, allowing readers to identify the chapters that relate to their interests. More specifically, the book distinguishes between two key drivers of environmentally responsibility: Profit and Regulatory compliance. The book is divided into five sections. The first three sections of the book explore profit driven environmental responsibility, and provide examples as to where the motives for environmentally responsible business practices come from, where business opportunities are, and what operational perspectives are key to profitability. The last two sections of the book focus on regulation as a driver of environmental responsibility and identify motives, opportunities, or operational perspectives as to effective regulatory compliance. Ultimately the book introduces the reader to the fundamentals of sustainable operations and highlights the latest research on the topic.

This book offers a comprehensive introduction to decision-making in an MCDM framework. Designed as a tutorial, it presents the main concepts and methods to be applied, together with essential background information. This includes the concept of nondominance, Simon's bounded rationality, Tversky and Kahneman's prospect theory, and the concepts of behavioral vs. mathematical convergence and premature stopping put forward by Korhonen, Moskowitz and Wallenius. The book concludes with a non-technical review of many popular decision algorithms, including the Analytic Hierarchy Process (AHP), VIMDA, and a number of classic interactive man-machine algorithms. In essence, the book is a "one-stop" source on everything you need to know about managerial decision-making in the multiple-criteria setting.

Decision-making is an important task no matter the industry. Operations research, as a discipline, helps alleviate decision-making problems through the extraction of reliable information related to the task at hand in order to come to a viable solution. Integrating stochastic processes into operations research and management can further aid in the decision-making process for industrial and management problems. Stochastic Processes and Models in Operations Research emphasizes mathematical tools and equations relevant for solving complex problems within business and industrial settings. This research-based publication aims to assist scholars, researchers, operations managers, and graduate-level students by providing comprehensive exposure to the concepts, trends, and technologies relevant to stochastic process modeling to solve operations research problems.

This volume provides a complete record of presentations made at Industrial Engineering, Management Science and Applications 2015 (ICIMSA 2015), and provides the reader with a snapshot of current knowledge and state-of-the-art results in industrial engineering, management science and applications. The goal of ICIMSA is to provide an excellent international forum for researchers and practitioners from both academia and industry to share cutting-edge developments in the field and to exchange and distribute the latest research and theories from the international community. The conference is held every year, making it an ideal platform for people to share their views and experiences in industrial engineering, management science and applications related fields.

This book is the seventh volume in a series entitled "Contemporary Logistics in China," authored by researchers from the Logistics Center at Nankai University. In the spirit of the six preceding annual volumes, this book carries on the ideal of providing a systematic exposition on the logistics development in China for the English-speaking community at large. Specially, this volume captures China's logistics development at a crucial turning point. On the one hand, it reflects the new horizon advocated by the Government's One-Belt-One-Road Initiative global cooperation strategy; on the other, it explores the Internet revolution, which has had major impacts on e-commerce and urban logistics in China. Subjects covered in this volume encompass the macro-factors pertaining to logistics development, region-specific plans, industry-wide transformation, globally-oriented moves, and current hot topics. The expositions on and analyses of these subjects are based on the latest available sources and statistical data. As with the previous volumes, the ultimate aim of this book is to present a timely portrait of the rapid growth of China's logistics market and the status quo of its logistics industry. In so doing, the book offers an in-depth analysis of critical issues involved in the ongoing dynamic and multi-faceted development, and provides a valuable reference resource for interested readers in the academic and professional fields.

This book shows how common operation management methods and algorithms can be extended to deal with vague or imprecise information in decision-making problems. It describes how to combine decision trees, clustering, multi-attribute decision-making algorithms and Monte Carlo Simulation with the mathematical description of imprecise or vague information, and how to visualize such information. Moreover, it discusses a broad spectrum of real-life management problems including forecasting the apparent consumption of steel products, planning and scheduling of production processes, project portfolio selection and economic-risk estimation. It is a concise, yet comprehensive, reference source for researchers in decision-making and decision-makers in business organizations alike.

The book gives a systematic and detailed description of a new integrated product and process development approach for sheet metal manufacturing. Special attention is given to manufacturing that unites multidisciplinary competences of product design, material science, and production engineering, as well as mathematical optimization and computer based information technology. The case study of integral sheet metal structures is used by the authors to introduce the results related to the recent manufacturing technologies of linear flow splitting, bend splitting, and corresponding integrated process chains for sheet metal structures.

This book introduces the reader to the field of multiobjective optimization through problems with simple structures, namely those in which the objective function and constraints are linear. Fundamental notions as well as state-of-the-art advances are presented in a comprehensive way and illustrated with the help of numerous examples. Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided at the end of each chapter, helping students to grasp and apply key concepts and methods to more complex problems. The book was motivated by the fact that the majority of the practical problems we encounter in management science, engineering or operations research involve conflicting criteria and therefore it is more convenient to formulate them as multicriteria optimization models, the solution concepts and methods of which cannot be treated using traditional mathematical programming approaches.

This book offers a comprehensive overview of quality and quality management. It also explores total quality management, covering its human, technological and analytical imperatives. It also examines quality systems and system standards, highlighting essential features and avoiding a reproduction of the ISO 9000 standard, as well as people-related issues in implementing a quality system. A holistic understanding of quality considerations, which now permeate every aspect of human life, should guide related policies, plans and practices. The book describes the all-pervasive characteristics of quality, putting together diverse definitions of "quality," outlining its different dimensions, and linking it with reliability and innovation. It goes on to assess the quality of measurements in terms of precision, accuracy and uncertainty and discusses managing quality with a focus on business performance. This is followed by a chapter on improving process quality, which is the summum bonum of quality management, and a chapter addressing the crucial problem of measuring customer satisfaction through appropriate models and tools. Further, it covers non-traditional subjects such as quality of life, quality of working life, quality assurance and improvement in education, with special reference to higher education, quality in research and development and characterizes the quality-related policies and practices in Indian industry. The last chapter provides a broad sketch of some recent advances in statistical methods for quality management. Along with the research community, the book's content is also useful for practitioners and industry watchers.

This book provides a comprehensive introduction to nonlinear programming, featuring a broad range of applications and solution methods in the field of continuous optimization. It begins with a summary of classical results on unconstrained optimization, followed by a wealth of applications from a diverse mix of fields, e.g. location analysis, traffic planning, and water quality management, to name but a few. In turn, the book presents a formal description of optimality conditions, followed by an in-depth discussion of the main solution techniques. Each method is formally described, and then fully solved using a numerical example.

This proceedings volume highlights the role and importance of Operational Research (OR) in the digital era and the underlying ICT challenges. The selected papers cover recent advances in all branches of operational research, mathematical modeling and decision making. It covers a wide range of key areas from digital economy, to supply chain management, and also finance. The book adopts an applied perspective that covers the contributions of OR in the broad field of business and economics linked with the discipline of computer science. The chapters are based on papers presented at the 6th International Symposium & 28th National Conference on Operational Research. Although the conference is organized by the Hellenic Operational Research Society (HELORS), the contributions in this book promotes international co-operation among researchers and practitioners working in the field.

The book presents a broad view on the nature of intelligent decision-making which is characterized by the use of models and methods in the framework of decision support for management. Contributions to this volume dedicated to Paul StAhly on the occasion of his 65th birthday include theoretical research and applications in optimization, operations research as well as decision support and management systems.

This edited book examines the challenges and opportunities arising from today's sharing economy from an operations management perspective. Individual chapter authors present state-of-the-art research that examines the general impact of sharing economy on production and consumption; the intermediary role of a sharing platform; crowdsourcing management; and context-based operational problems. Sharing economy refers to a market model that enables and facilitates the sharing of access to goods and services. For example, Uber allows riders to share a car. Airbnb allows homeowners to share their extra rooms with renters. Groupon crowdsources demands, enabling customers to share the benefit of discounted goods and services, whereas Kickstarter crowdsources funds, enabling backers to fund a project jointly. Unlike the classic supply chain settings in which a firm makes inventory and supply decisions, in sharing economy, supply is crowdsourced and can be modulated by a platform. The matching-supply-with-demand process in a sharing economy requires novel perspectives and tools to address challenges and identify opportunities. The book is comprised of 20 chapters that are divided into four parts. The first part explores the general impact of sharing economy on the production, consumption, and society. The second part explores the intermediary role of a sharing platform that matches crowdsourced supply with demand. The third part investigates the crowdsourcing management on a sharing platform, and the fourth part is dedicated to context-based operational problems of popular sharing economy applications. "While sharing economy is becoming omnipresence, the operations management (OM) research community has begun to explore and examine different business models in the transportation, healthcare, financial, accommodation, and sourcing sectors. This book presents a collection of the state-of-the-art research work conducted by a group of world-leading OM researchers in this area. Not only does this book cover a wide range of business models arising from the sharing economy, but it also showcases different modeling frameworks and research methods that cannot be missed. Ultimately, this book is a tour de force - informative and insightful!" Christopher S. Tang Distinguished Professor and Edward Carter Chair in Business Administration UCLA Anderson School of Management

This book provides theoretical and practical insights for effective decision making in situations that involve various types of conflict cleavages. Embedding historical analysis, negotiation analysis, political scientific analysis and game theoretical analysis in an integrated analytical framework allows a comprehensive perspective on various dilemmas and self-enforcing dynamics that inhibit decision making. The conceptualization of strategic facilitation highlights the value of leadership, chairmanship and the role of threshold states in facilitating decision making as the global climate change negotiations unfolds.

To ensure the security and economy of future power system operation in the context of a high degree of renewable energy penetration, this thesis proposes a new distributed algorithm called generalized master-slave-splitting (G-MSS) theory and a new transmission-distribution coordinated energy management (TDCEM) method that is based on the G-MSS theory. The thesis studies the mathematical properties of the G-MSS theory in detail. Based on the G-MSS theory, a distributed TDCEM method - which involves distributed security analysis, distributed voltage stability analysis, distributed economic dispatch and distributed optimal power flow for an integrated transmission-distribution system - is then developed for the first time. The thesis demonstrates that the proposed TDCEM method significantly contributes to more reliable and optimal operation in power systems. The book will benefit researchers, scientists and engineers in the field of power system operation and optimization.

This book is a comprehensive introduction of the reader into the simulation and modelling techniques and their application in the management of organisations. The book is rooted in the thorough understanding of systems theory applied to organisations and focuses on how this theory can apply to econometric models used in the management of organisations. The econometric models in this book employ linear and dynamic programming, graph theory, queuing theory, game theory, etc. and are presented and analysed in various fields of application, such as investment management, stock management, strategic decision making, management of production costs and the lifecycle costs of quality and non-quality products, production quality Management, etc.

This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.

This book provides readers with a timely and comprehensive yet concise view on the field of fuzzy logic and its real-world applications. The chapters, written by authoritative scholars in the field, report on promising new models for data analysis, decision making, and systems modeling, with a special emphasis on their applications in management science. The book is a token of appreciation from the fuzzy research community to Professor Christer Carlsson for his long time research and organizational commitment, which have among other things resulted in the foundation and success of the Institute for Advanced Management Systems Research (IAMSR) at Abo Akademi University, in Abo (Turku), Finland. The book serves as timely guide for the fuzzy logic and operations research communities alike.

Although several books or monographs on multiobjective optimization under uncertainty have been published, there seems to be no book which starts with an introductory chapter of linear programming and is designed to incorporate both fuzziness and randomness into multiobjective programming in a unified way. In this book, five major topics, linear programming, multiobjective programming, fuzzy programming, stochastic programming, and fuzzy stochastic programming, are presented in a comprehensive manner. Especially, the last four topics together comprise the main characteristics of this book, and special stress is placed on interactive decision making aspects of multiobjective programming for human-centered systems in most realistic situations under fuzziness and/or randomness.

Organization of each chapter is briefly summarized as follows: Chapter 2 is a concise and condensed description of the theory of linear programming and its algorithms. Chapter 3 discusses fundamental notions and methods of multiobjective linear programming and concludes with interactive multiobjective linear programming. In Chapter 4, starting with clear explanations of fuzzy linear programming and fuzzy multiobjective linear programming, interactive fuzzy multiobjective linear programming is presented. Chapter 5 gives detailed explanations of fundamental notions and methods of stochastic programming including two-stage programming and chance constrained programming. Chapter 6 develops several interactive fuzzy programming approaches to multiobjective stochastic programming problems. Applications to purchase and transportation planning for food retailing are considered in Chapter 7.

The book is self-contained because of the three appendices and answers to problems. Appendix A contains a brief summary of the topics from linear algebra. Pertinent results from nonlinear programming are summarized in Appendix B. Appendix C is a clear explanation of the Excel Solver, one of the easiest ways to solve optimization problems, through the use of simple examples of linear and nonlinear programming.

This book presents papers based on the presentations and discussions at the international workshop on Big Data Smart Transportation Analytics held July 16 and 17, 2016 at Tongji University in Shanghai and chaired by Professors Ukkusuri and Yang. The book is intended to explore a multidisciplinary perspective to big data science in urban transportation, motivated by three critical observations: The rapid advances in the observability of assets, platforms for matching supply and demand, thereby allowing sharing networks previously unimaginable. The nearly universal agreement that data from multiple sources, such as cell phones, social media, taxis and transit systems can allow an understanding of infrastructure systems that is critically important to both quality of life and successful economic competition at the global, national, regional, and local levels. There is presently a lack of unifying principles and methodologies that approach big data urban systems. The workshop brought together varied perspectives from engineering, computational scientists, state and central government, social scientists, physicists, and network science experts to develop a unifying set of research challenges and methodologies that are likely to impact infrastructure systems with a particular focus on transportation issues. The book deals with the emerging topic of data science for cities, a central topic in the last five years that is expected to become critical in academia, industry, and the government in the future. There is currently limited literature for researchers to know the opportunities and state of the art in this emerging area, so this book fills a gap by synthesizing the state of the art from various scholars and help identify new research directions for further study.

This is a new edition of Kleijnen's advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Altogether, this new edition has approximately 50% new material not in the original book. More specifically, the author has made significant changes to the book's organization, including placing the chapter on Screening Designs immediately after the chapters on Classic Designs, and reversing the order of the chapters on Simulation Optimization and Kriging Metamodels. The latter two chapters reflect how active the research has been in these areas. The validation section has been moved into the chapter on Classic Assumptions versus Simulation Practice, and the chapter on Screening now has a section on selecting the number of replications in sequential bifurcation through Wald's sequential probability ration test, as well as a section on sequential bifurcation for multiple types of simulation responses. Whereas all references in the original edition were placed at the end of the book, in this edition references are placed at the end of each chapter. From Reviews of the First Edition: "Jack Kleijnen has once again produced a cutting-edge approach to the design and analysis of simulation experiments." (William E. BILES, JASA, June 2009, Vol. 104, No. 486)

This book offers a timely overview of fuzzy and rough set theories and methods. Based on selected contributions presented at the International Symposium on Fuzzy and Rough Sets, ISFUROS 2017, held in Varadero, Cuba, on October 24-26, 2017, the book also covers related approaches, such as hybrid rough-fuzzy sets and hybrid fuzzy-rough sets and granular computing, as well as a number of applications, from big data analytics, to business intelligence, security, robotics, logistics, wireless sensor networks and many more. It is intended as a source of inspiration for PhD students and researchers in the field, fostering not only new ideas but also collaboration between young researchers and institutions and established ones.

This book introduces a new paradigm called 'Optimization in Changeable Spaces' (OCS) as a useful tool for decision making and problem solving. It illustrates how OCS incorporates, searches, and constructively restructures the parameters, tangible and intangible, involved in the process of decision making. The book elaborates on OCS problems that can be modeled and solved effectively by using the concepts of competence set analysis, Habitual Domain (HD) and the mental operators called the 7-8-9 principles of deep knowledge of HD. In addition, new concepts of covering and discovering processes are proposed and formulated as mathematical tools to solve OCS problems. The book also includes reformulations of a number of illustrative real-life challenging problems that cannot be solved by traditional optimization techniques into OCS problems, and details how they can be addressed. Beyond that, it also includes perspectives related to innovation dynamics, management, artificial intelligence, artificial and e-economics, scientific discovery and knowledge extraction. This book will be of interest to managers of businesses and institutions, policy makers, and educators and students of decision making and behavior in DBA and/or MBA.

This book shows how transit assignment models can be used to describe and predict the patterns of network patronage in public transport systems. It provides a fundamental technical tool that can be employed in the process of designing, implementing and evaluating measures and/or policies to improve the current state of transport systems within given financial, technical and social constraints. The book offers a unique methodological contribution to the field of transit assignment because, moving beyond "traditional" models, it describes more evolved variants that can reproduce:* intermodal networks with high- and low-frequency services;* realistic behavioural hypotheses underpinning route choice;* time dependency in frequency-based models; and* assumptions about the knowledge that users have of network conditionsthat are consistent with the present and future level of information that intelligent transport systems (ITS) can provide. The book also considers the practical perspective of practitioners and public transport operators who need to model and manage transit systems; for example, the role of ITS is explained with regard to their potential in data collection for modelling purposes and validation techniques, as well as with regard to the additional data on network patronage and passengers' preferences that influences the network-management and control strategies implemented. In addition, it explains how the different aspects of network operations can be incorporated in traditional models and identifies the advantages and disadvantages of doing so. Lastly, the book provides practical information on state-of-the-art implementations of the different models and the commercial packages that are currently available for transit modelling. Showcasing original work done under the aegis of the COST Action TU1004 (TransITS), the book provides a broad readership, ranging from Master and PhD students to researchers and from policy makers to practitioners, with a comprehensive tool for understanding transit assignment models.