Like norms, translation invariant functions are a natural and powerful tool for the separation of sets and scalarization. This book provides an extensive foundation for their application. It presents in a unified way new results as well as results which are scattered throughout the literature. The functions are defined on linear spaces and can be applied to nonconvex problems. Fundamental theorems for the function class are proved, with implications for arbitrary extended real-valued functions. The scope of applications is illustrated by chapters related to vector optimization, set-valued optimization, and optimization under uncertainty, by fundamental statements in nonlinear functional analysis and by examples from mathematical finance as well as from consumer and production theory. The book is written for students and researchers in mathematics and mathematical economics. Engineers and researchers from other disciplines can benefit from the applications, for example from scalarization methods for multiobjective optimization and optimal control problems.

This book presents recent work that analyzes general issues of green logistics and smart cities. The contributed chapters consider operating models with important ecological, economic, and social objectives. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

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Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today's state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.

This book focuses on the latest advances in nonlinear dynamic modeling in economics and finance, mainly-but not solely-based on the description of strategic interaction by using concepts and methods from dynamic and evolutionary game theory. The respective chapters cover a range of theoretical issues and examples concerning how the qualitative theory of dynamical systems is used to analyze the local and global bifurcations that characterize complex behaviors observed in social systems where heterogeneous and boundedly rational economic agents interact. Nonlinear dynamical systems, represented by difference and differential and functional equations, are extensively used to simulate the behavior of time-evolving economic systems, also in the presence of time lags, discontinuities, and hysteresis phenomena. In addition, some theoretical issues and particular applications are discussed, as well. The contributions gathered here offer an up-to-date review of the latest research in this rapidly developing research area.

This textbook introduces systems science as an entry point to present a basic introduction to research models and methods in management science (operation research). This textbook selects the classic quantitative models and methods as well as rich cases and detailed examples, which are suitable for students with a certain management and economics knowledge for further study, and helps to develop the abilities of using the basic models in real life.

In order to experience significant improvement in business processes, successful organizations must launch, implement, and maintain effective transformation programs. Such programs enable companies to fully maximize benefits and avoid potential failures. Optimization of Supply Chain Management in Contemporary Organizations discusses best practices and methods in transformation initiatives that improve the overall functionality and success of supply chain processes. Focusing on performance measurement, change management, and strategy development, this book is an essential reference source for executives, managers, advanced-level students, and professionals working in the field of business transformations and supply chain development.

Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting; Introduces applied optimization to the hazardous waste blending problem; Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control; Includes an extensive bibliography at the end of each chapter and an index; GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8; Solutions manual available upon adoptions.

This book outlines the latest trends in the use of multicriteria analysis in agriculture by highlighting recent applications for modeling agricultural decision-making. It introduces specific case studies using multicriteria analysis as a method for selecting multiattribute discrete alternatives or solving multiobjective planning problems. The book is intended for a broad readership, including agricultural and environmental economists, engineers and all scientists whose work involves the management of agricultural resources and decision-making in agriculture. The methods and applications presented in this book cover decision-making processes in agricultural and environmental contexts. The methodologies described consider multiple criteria simultaneously in a wide range of complex decision-making contexts by taking into account multiple, conflicting criteria. Given the wide range of case studies covered, the book offers a comprehensive guide to decision-making in the agricultural context and beyond.

This book explores the methodological and application developments of network design in transportation and logistics. It identifies trends, challenges and research perspectives in network design for these areas. Network design is a major class of problems in operations research where network flow, combinatorial and mixed integer optimization meet. The analysis and planning of transportation and logistics systems continues to be one of the most important application areas of operations research. Networks provide the natural way of depicting such systems, so the optimal design and operation of networks is the main methodological area of operations research that is used for the analysis and planning of these systems. This book defines the current state of the art in the general area of network design, and then turns to its applications to transportation and logistics. New research challenges are addressed. Network Design with Applications to Transportation and Logistics is divided into three parts. Part I examines basic design problems including fixed-cost network design and parallel algorithms. After addressing the basics, Part II focuses on more advanced models. Chapters cover topics such as multi-facility network design, flow-constrained network design, and robust network design. Finally Part III is dedicated entirely to the potential application areas for network design. These areas range from rail networks, to city logistics, to energy transport. All of the chapters are written by leading researchers in the field, which should appeal to analysts and planners.

This handbook covers DEA topics that are extensively used and solidly based. The purpose of the handbook is to (1) describe and elucidate the state of the field and (2), where appropriate, extend the frontier of DEA research. It defines the state-of-the-art of DEA methodology and its uses. This handbook is intended to represent a milestone in the progression of DEA. Written by experts, who are generally major contributors to the topics to be covered, it includes a comprehensive review and discussion of basic DEA models, which, in the present issue extensions to the basic DEA methods, and a collection of DEA applications in the areas of banking, engineering, health care, and services. The handbook's chapters are organized into two categories: (i) basic DEA models, concepts, and their extensions, and (ii) DEA applications. First edition contributors have returned to update their work.

The second edition includes updated versions of selected first edition chapters. New chapters have been added on: different approaches with no need for a priori choices of weights (called multipliers) that reflect meaningful trade-offs, construction of static and dynamic DEA technologies, slacks-based model and its extensions, DEA models for DMUs that have internal structures network DEA that can be used for measuring supply chain operations, Selection of DEA applications in the service sector with a focus on building a conceptual framework, research design and interpreting results.

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This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.

Executives' morality and ethics became major research topics following recent business scandals, but the research missed a major explanation of executives' immorality: career advancement by "jumping" between firms that causes ignorance of job-pertinent tacit local knowledge, tempting "jumpers" to covertly conceal this ignorance. Generating distrust and ignorance cycles and mismanagement, this choice bars performance-based career advancement and encourages immoral careerism, advancing by immoral subterfuges. Such careerism is a known managerial malady, but explaining its emergence proved challenging as managerial ignorance is covertly concealed as a dark secret on organizations' dark side by conspiracies of silence. Managerially educated and experienced, Dr. Shapira achieved a breakthrough by a 5-year semi-native anthropological study of five "jumper"-managed automatic processing plants and their parent firms. This book untangles common ignorance and immoral careerism, concealed as dark secrets by executives who "rode" on the successes of mid-level "jumpers" who high-morally risked their authority and power by admitting ignorance and trustfully learned local tacit knowledge. The opposite choice tendencies accorded power, authority, and status rankings, which made practicing immorality easier the higher one's position, suggesting that the common "jumping" between managerial careers nurtures immoral executives similar to those exposed in the recent business scandals.

This book provides the readers with the overall latest research on think tanks, summarizing the characteristics of think tanks, revealing the general laws and internal logic of think tank research, applying systems, dialectical views and operations research, system theory, and cybernetics to the problems existing in the research work of think tanks at home and abroad. Based on problem-oriented, evidence-oriented and scientific orientation, this book systematically considers the methodology of think tank research, proposes the DIIS theoretical method system of think tank research, defines the standardization process of think tank research and the quality standard of think tank DIIS, and gives corresponding DIIS to the actual think tank research problem. The method aims to improve the scientificity, effectiveness, and reliability of the research results of think tanks, provide systematic theoretical analysis for think tank research, promote the professional development of think tanks, and better serve the modernization of national governance systems and governance capabilities. This book presents new theoretical and research method support and reference that contribute to macro decision-making departments, management departments, scientific research institutes, universities, and enterprises think tank research related departments, strategic decision makers, think tank managers, think tank researchers, and readers interested in think tanks reading and using. Finally yet importantly, this book embodies the research of think tank as the object of investigation, jumping out of specific social conditions, using systemic thoughts, thinking about the more general role and characteristics of think tanks from the theoretical level, important theoretical issues such as principles and logic systems that think tank research should follow.

This series publishes monograph-length conceptual papers designed to promote theory and research on important substantive and methodological topics in the field of human resources management. Volume 21 contains eight papers on critical issues in the field of human resources management, thus continuing the tradition of the series to develop a more informed understanding of the field.

Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research. The use of hidden Markov models (HMMs) has become one of the hottest areas of research for such applications to finance. This handbook offers systemic applications of different methodologies that have been used for decision making solutions to the financial problems of global markets. As the follow-up to the authors' Hidden Markov Models in Finance (2007), this offers the latest research developments and applications of HMMs to finance and other related fields. Amongst the fields of quantitative finance and actuarial science that will be covered are: interest rate theory, fixed-income instruments, currency market, annuity and insurance policies with option-embedded features, investment strategies, commodity markets, energy, high-frequency trading, credit risk, numerical algorithms, financial econometrics and operational risk. Hidden Markov Models in Finance: Further Developments and Applications, Volume II presents recent applications and case studies in finance and showcases the formulation of emerging potential applications of new research over the book's 11 chapters. This will benefit not only researchers in financial modeling, but also others in fields such as engineering, the physical sciences and social sciences. Ultimately the handbook should prove to be a valuable resource to dynamic researchers interested in taking full advantage of the power and versatility of HMMs in accurately and efficiently capturing many of the processes in the financial market.

Until recently most observers were of the opinion that firms had to adopt a Japanese model of management or perish. They overlooked the fact that there are a number of efficient productive models and that there is no single 'best way'. This book shows the diversity of productive models and discusses the optimum macro and micro economic and social conditions that a firm needs to stay profitable. In conclusion the authors suggest an analytical framework of profitability conditions, easily accessible to practitioners, academics and students.

These proceedings focus on selected aspects of the current and upcoming trends in transportation, logistics, supply chain management, and decision sciences. In detail the included scientific papers analyze the problem of Decision Making under Uncertainty, Stochastic Optimization, Transportation, Logistics and Intelligent Business. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of the symposium "The Seventh International Forum on Decision Sciences", which took place in Windsor, Canada.

This pioneering book on food study pursues an interdisciplinary approach to service science and the service engineering field. Further, it highlights a range of experiments conducted at actual business sites to verify the effectiveness of the proposed methodologies and theories. In modern society, food study has become more complex, as it involves multiple fields of science. For instance, a long-lived society entails a number of problems for human beings. A balanced intake of nutrients is important for a healthy life, but in many cases, healthy food is not the most enjoyable. As such, it is important for the food industry to provide foods that are both tasty and wholesome, based on the sciences of gastronomy and nutrition. Conventional food study proceeds along the lines of a specific field such as nutrition, agriculture, or gastronomy, though it should be conducted in an interdisciplinary manner. This book covers multifaceted research on food study to respond to today's societal demands, based mainly on the natural and social sciences. It addresses a wide range of topics, including: food production management using mathematical modeling, operations research, and production engineering; evaluation of food products based on big data analysis; psychological experiments and ethnography; food products based on consumer behavior; organoleptic assessment and health improvement; design of physical dining environments using virtual reality, pedestrian debt recognition (human indoor position measuring), and observation of behavior. Reporting on and assessing many studies conducted at actual business locations, the book offers a unique and highly practical resource.

This book takes a unique approach to linear optimization by focusing on the underlying principles and business applications of a topic more often taught from a mathematical and computational perspective. By shifting the perspective away from heavy math, students learn how optimization can be used to drive decision making in real world business settings. The book does not shy away from the theory underlying linear optimization but rather focuses on ensuring students understand the logic without getting caught up in proving theorems. Plenty of examples, applications and case studies are included to help bridge the gap between the theory and the way it plays out in practice. The author has also included several Excel spreadsheets, showing worked-out models of linear optimization that have been used to drive decisions ranging from configuring a police force to purchasing crude oil and media planning. How can the routes and pricing structures of airlines be optimized? How much should be invested in the prevention and punishment of crimes? These are everyday problems that can be solved using linear optimization, and this book shows students just how to do that. It will prove a useful, math-free resource for all students of management science and operations research.

Large-Scale Nonlinear Optimization reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research. The chapters of the book, authored by some of the most active and well-known researchers in nonlinear optimization, give an updated overview of the field from different and complementary standpoints, including theoretical analysis, algorithmic development, implementation issues and applications.

Games, or contexts of strategic interaction, pervade and suffuse our lives and the lives of all organisms. How are we to make sense of and cope with such situations? How should an agent play? When will and when won't cooperation arise and be maintained? Using examples and a careful digestion of the literature, Agents, Games, and Evolution: Strategies at Work and Play addresses these encompassing themes throughout, and is organized into four parts: Part I introduces classical game theory and strategy selection. It compares ideally rational and the "naturalist" approach used by this book, which focuses on how actual agents chose their strategies, and the effects of these strategies on model systems. Part II explores a number of basic games, using models in which agents have fixed strategies. This section draws heavily on the substantial literature associated with the relevant application areas in the social sciences. Part III reviews core results and applications of agent-based models in which strategic interaction is present and for which design issues have genuine practical import. This section draws heavily on the substantial literature associated with the application area to hand. Part IV addresses miscellaneous topics in strategic interaction, including lying in negotiations, reasoning by backward induction, and evolutionary models. Modeled after the authors' Agents, Games, and Evolution course at the University of Pennsylvania, this book keeps mathematics to a minimum, focusing on computational strategies and useful methods for dealing with a variety of situations.

Evidence-Based Decision-Making: How to Leverage Available Data and Avoid Cognitive Biases examines how a wide range of factual evidence, primarily derived from a variety of data available to organizations, can be used to improve the quality of business decision-making, by helping decision makers circumvent the various cognitive biases that adversely impact how we all think. The book is built on the following premise: During the past decade, the new 'data world' emerged, in which the rush to develop competencies around business analytics and data science can be characterized as nothing less than the new commercial arms race. The ever-expanding volume and variety of data are well known, as are the great advances in data processing/analytics, data visualization, and related information production-focused capabilities. Yet, comparatively little effort has been devoted to how the informational products of business analytics and data science are 'consumed' or used in the organizational decision-making processes, as the available evidence shows that only some of that information is used to drive some business decisions some of the time. Evidence-Based Decision-Making details an explicit process describing how the universe of available and applicable evidence, which includes organizational and other data, industry benchmarks, scientific studies, and professional experience, can be assessed, amalgamated, and funneled into an objective driver of key business decisions. Introducing key concepts in relation to data and evidence, and the history of evidence-based management, this new and extremely topical book will be essential reading for researchers and students of data analytics as well as those working in the private and public sectors, and in the voluntary sector.

Diverse kinds of knowledge are vital for each organization that would successfully compete today in an international scenario. The emergent relevance of knowledge and its management in an even more complex environment opens up the possibility to analyze, investigate and deepen our understanding on different aspects related to several functional areas in business management. Nowadays, firms that create new knowledge and apply it effectively and efficiently will be successful at creating competitive advantages. The choices of the firms in selecting and applying different knowledge process (such as knowledge sourcing, transferring and exploiting) as well as knowledge tools may be crucial. Thus, the role of knowledge as the key source of potential advantage for organizations and indeed whole economies is still a hot debate in the international landscape. This book develops insights for the management of knowledge in cross-functional business areas to originate an innovative approach to the classical Knowledge Management (KM) field. This book provides a fresh perspective on different knowledge related topics in an international landscape, highlighting the key role of knowledge and its management in business activities. Overall, the primary aim of this book is to extend our understandings on how KM can be helpful in several cross-functional management areas, such as strategic management, finance, HRM and innovation as well as in different business circumstances such as M&A, internationalization processes and risk management.

This textbook provides an innovative pedagogy to students who will be the policy makers of tomorrow. It provides thoughts on sustainability and the complexity among its different dimensions. It guides students through experience, processes of complex decision making, and sharpen their clarity of thought, to enhance their communication abilities and help them develop critical thinking. It provides key competencies to address the complexities of sustainable development. By combining game-based learning with an analytical style of education, supplemental materials are provided to make the definitions of various sustainability aspects more concrete and allows students to experiment in a consequence-free environment, with scenario examples. Board Game and a hypothetical management course, dealing with various topics like transportation sustainability, societal metabolism, etc. as well as with decision making under those contexts, will formalize the mathematics needed to make robust decisions.