Data and its processed state 'information' have become an indispensable resource for virtually all aspects of business, education, etc. Consequently, decisions regarding the handling of this data, transforming it into meaningful information, and ultimately arriving at the best course of action have taken on a new importance. This book highlights a selection of cutting-edge research on decision making presented at the 25th International Conference on Multiple Criteria Decision Making (MCDM 2019), held in Istanbul, Turkey.

Introductory courses in combinatorial optimization are popular at the upper undergraduate/graduate levels in computer science, industrial engineering, and business management/OR, owed to its wide applications in these fields. There are several published textbooks that treat this course and the authors have used many of them in their own teaching experiences. This present text fills a gap and is organized with a stress on methodology and relevant content, providing a step-by-step approach for the student to become proficient in solving combinatorial optimization problems. Applications and problems are considered via recent technology developments including wireless communication, cloud computing, social networks, and machine learning, to name several, and the reader is led to the frontiers of combinatorial optimization. Each chapter presents common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, as well as key algorithms, such as greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in every chapter, strategically placed graphics, and an extensive bibliography are amongst the gems of this textbook.

With European Monetary Union well underway, Europe is starting to look at nearby countries and culturally closer continents to define its strategies for the future.
In this book, chapters by leading Mexican economists are matched with reactions from European colleagues. They offer a novel viewpoint on the critical assessment of the North American Free Trade Area (NAFTA) process, and its implications for the economies of the two continents.

eBook available with sample pages: 0203187830

The volume examines the state-of-the-art of productivity and efficiency analysis. It brings together a selection of the best papers from the 10th North American Productivity Workshop. By analyzing world-wide perspectives on challenges that local economies and institutions may face when changes in productivity are observed, readers can quickly assess the impact of productivity measurement, productivity growth, dynamics of productivity change, measures of labor productivity, measures of technical efficiency in different sectors, frontier analysis, measures of performance, industry instability and spillover effects. The contributions in this volume focus on the theory and application of economics, econometrics, statistics, management science and operational research related to problems in the areas of productivity and efficiency measurement. Popular techniques and methodologies including stochastic frontier analysis and data envelopment analysis are represented. Chapters also cover broader issues related to measuring, understanding, incentivizing and improving the productivity and performance of firms, public services, and industries.

This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.

The effectiveness of policy decisions depends not only on the quality of the analysis but also on the communication between analyst and decision-maker. As a result, this book employs the following three-step decomposition of the decision modeling process throughout the book: (1) visual-structural modeling, (2) analytic-formal modeling, and (3) algorithmic resolution modeling. The 10 chapters address the most relevant issues in decision modeling in policy management: the problem-solving process, visual decision modeling, descriptive and normative preference elicitation and aggregation methods, dealing with uncertainty in dynamic problems, social choices, conflict resolution, and constraint-optimization problems. A problem-oriented engineering approach has been taken throughout the book because this approach covers the most popular decision modeling issues in: (1) decision analysis (decision trees, probabilistic influence diagrams, fuzzy decision-making, risk analysis), (2) operations research (facility location, scheduling, linear and non-linear programming, network optimization), and (3) economics (cost-benefit analysis, capital budgeting, shadow prices, marginal rate of substitution, net present value, game theory). Decision Modeling in Policy Management: Introduces a visual approach to decision modeling in policy management (over 100 figures and illustrations), integrating the European School (outranking relations, dimension reduction, ordinal preferences, rank correlation) and the American School (utility theory, analytic hierarchy process, game theory, constraint-optimization). Presents analytic approaches in the context of structural, formal, and resolution modeling; references tofurther practical and theoretical readings; intuitive visual reasoning; detailed numerical examples replacing theorems and formal proofs. Discusses new decision analytical features: visual interactive preference ordering; dynamic plots in virtual negotiation; hypermedia influence diagram modeling. Integrates 100 problems with worked-out solutions; an Internet syllabus with assignments, students comments, and Internet multimedia software are available.

Currently the methods of Soft Computing are successfully used for risk analysis in: budgeting, e-commerce development, portfolio selection, Black-Scholes option pricing models, corporate acquisition systems, evaluating investments in advanced manufacturing technology, interactive fuzzy interval reasoning for smart web shopping, fuzzy scheduling and logistic.
An essential feature of economic and financial problems it that there are always at least two criteria to be taken into account: profit maximization and risk minimization. Therefore, the economic and financial problems are multiple criteria ones. In this book, a new systematization of the problems of multiple criteria decision making is proposed which allows the author to reveal unsolved problems. The solutions of them are presented as well and implemented to deal with some important real-world problems such as investment project's evaluation, tool steel material selection problem, stock screening and fuzzy logistic.
It is well known that the best results in real -world applications can be obtained using the synthesis of modern methods of soft computing. Therefore, the developed by the author new approach to building effective stock trading systems, based on the synthesis of fuzzy logic and the Dempster-Shafer theory, seems to be a considerable contribution to the application of soft computing method in economics and finance.
An important problem of capital budgeting is the fuzzy evaluation of the Internal Rate of Return. In this book, this problem is solved using a new method which makes it possible to solve linear and nonlinear interval and fuzzy equations and systems of them. The developed new method allows the author to obtain an effective solution of the Leontjev's input-output problem in the interval setting.
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This book provides a straightforward overview for every researcher interested in stochastic dynamic vehicle routing problems (SDVRPs). The book is written for both the applied researcher looking for suitable solution approaches for particular problems as well as for the theoretical researcher looking for effective and efficient methods of stochastic dynamic optimization and approximate dynamic programming (ADP). To this end, the book contains two parts. In the first part, the general methodology required for modeling and approaching SDVRPs is presented. It presents adapted and new, general anticipatory methods of ADP tailored to the needs of dynamic vehicle routing. Since stochastic dynamic optimization is often complex and may not always be intuitive on first glance, the author accompanies the ADP-methodology with illustrative examples from the field of SDVRPs. The second part of this book then depicts the application of the theory to a specific SDVRP. The process starts from the real-world application. The author describes a SDVRP with stochastic customer requests often addressed in the literature, and then shows in detail how this problem can be modeled as a Markov decision process and presents several anticipatory solution approaches based on ADP. In an extensive computational study, he shows the advantages of the presented approaches compared to conventional heuristics. To allow deep insights in the functionality of ADP, he presents a comprehensive analysis of the ADP approaches.

This book covers central issues in mitigating supply chain risks from various perspectives. Today's supply chains are vulnerable to disruptions that can have a significant impact on firms, business and performance. The aim of supply chain risk management is to identify the potential sources of risks and implement appropriate actions in order to mitigate supply chain disruptions. In this regard, the book presents a wealth of methods, strategies and analyses that are essential for mitigating supply chain risks. As a comprehensive collection of the latest research and cutting-edge developments in supply chain risk and its mitigation, the book is structured into four main parts, addressing supply chain risk strategies and developments; supply chain risk management review; supply chain sustainability and resilience; and supply chain analysis and risk management applications. The contributing authors are leading academic researchers and practitioners, who combine findings and research results with a practical and contemporary view on how companies can best manage supply chain risks and disruptions, as well as how to create resilient and sustainable supply chains. This book can be used as an essential resource for students and scholars who are interested in pursuing research or teaching courses on the rapidly growing field of supply chain management. It also offers an interesting and informative read for managers and practitioners who need to deepen their understanding of effective supply chain risk management.

This book is the first easy-to-read text on nonsmooth optimization (NSO, not necessarily di erentiable optimization). Solving these kinds of problems plays a critical role in many industrial applications and real-world modeling systems, for example in the context of image denoising, optimal control, neural network training, data mining, economics and computational chemistry and physics. The book covers both the theory and the numerical methods used in NSO and provide an overview of di erent problems arising in the eld. It is organized into three parts:

1. convex and nonconvex analysis and the theory of NSO;

2. test problems and practical applications;

3. a guide to NSO software.The book is ideal for anyone teaching or attending NSO courses. As an accessible introduction to the eld, it is also well suited as an independent learning guide for practitioners already familiar with the basics of optimization."

The efficiency of computational methods and the choice of the most efficient methods for solving a specific problem or a specific class of problems have always played an important role in numerical analysis. Optimization of the computerized solution process is now a major problem of applied mathematics, which stimulates the search for new computational methods and ways to implement them. In "Minimax Models in the theory of Numerical Methods", methods for estimating the efficiency of computational algorithms and problems of their optimality are studied within the framework of a general computation model. The subjects dealt with in this are very different from the traditional subjects of computational methods. Close attention is paid to adaptive (sequential) computational algorithms, the process of computation being regarded as a controlled process and the algorithm as a control strategy. This approach allows methods of game theory and other methods of operations research and systems analysis to be widely used for constructing optimal algorithms. The goal underlying the study of the various comutation models dealt with in this title is the construction of concrete numerical algorithms admitting programme implementation. The central role belongs to the concept of a sequentially optimal algorithms, which in many cases reflects the characterics of real-life computational processes more fully than the traditional optimality concepts.

Agile Business Analysis discusses trends in the business analysis and agile environments, how these two areas align and promote each other, and identifies areas of responsibility and ownership for the business analyst (BA). Readers will learn ways BAs can provide support to agile projects through modeling techniques; documentation; communication, meetings and reporting; governance; building user stories, elaborating requirements, and facilitating the estimating process; ensuring effective application of lessons, improvements, and efficiencies; and much more. The book is designed for BAs of all levels, from all types of environments.

This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates MESP in information theory, as the algorithmic problem of calculating a sub-vector of pre-specificed size from a multivariate Gaussian random vector, so as to maximize Shannon's differential entropy. The text collects and expands on state-of-the-art algorithms for MESP, and addresses its application in the field of environmental monitoring. While MESP is a central optimization problem in the theory of statistical designs (particularly in the area of spatial monitoring), this book largely focuses on the unique challenges of its algorithmic side. From the perspective of mathematical-optimization methodology, MESP is rather unique (a 0/1 nonlinear program having a nonseparable objective function), and the algorithmic techniques employed are highly non-standard. In particular, successful techniques come from several disparate areas within the field of mathematical optimization; for example: convex optimization and duality, semidefinite programming, Lagrangian relaxation, dynamic programming, approximation algorithms, 0/1 optimization (e.g., branch-and-bound), extended formulation, and many aspects of matrix theory. The book is mainly aimed at graduate students and researchers in mathematical optimization and data analytics.

As service centred organisations become and focused on the customer, values are co-created with their customers through organisational capabilities. The central part of these capabilities is knowledge which is directly supported by information technology and the relationships between the service firms' knowledge, capabilities, IT and strategy is essential for superior value co-creation with customers. Knowledge Driven Service Innovation and Management: IT Strategies for Business Alignment and Value Creation provides a comprehensive collection of research and analysis on the principles of service, knowledge and organisational capabilities. This book aims to clarify IT strategy procedures and management practices and how they are used to shape a firm's knowledge organisations as well as facilitate service innovation and customer value co-creation.

This book covers sustainable development in smart society's 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.

This book presents a selection of current research results in the field of intelligent systems and draws attention to their practical applications and issues connected with the areas of decision-making, economics, business and finance. The nature of the contributions is interdisciplinary - combining psychological and behavioural aspects with the theory and practice of decision-support, design of intelligent systems and development of machine learning tools. The authors, among other topics, discuss the multi-expert evaluation with intangible criteria, suggest a redefinition of the standard multiple-criteria decision-making framework, propose novel methods for causal map analysis and new feature selection methods. The topics are selected to stress the potential of the up-to-date intelligent methods to deal with practical problems relevant in these areas and to provide inspiration for advanced students, researchers and practitioners in the respective fields.

Contains case studies from engineering and operations research

Includes commented literature for each chapter

This book aims at providing cases with inspiring findings for global researchers in capacity allocation and reservation. Capacity allocation mechanisms are introduced in the book, as well as the measures to build models and the ways to achieve supply chain coordination. In addition, it illustrates the capacity reservation contract and quantity flexible contract with comparisons and some numerical studies. The book is divided into 7 chapters. Chapter 1 introduces the background and the latest development of the research. Chapter 2 introduces how to manage downstream competition through capacity allocation in symmetric market, including proportional mechanism and lexicographic mechanism. Demand competition is introduced in Chapter 3 as well as the uniform allocation mechanism and the comparisons among three different mechanisms. In Chapter 4, we give information about demand competition with fixed factor allocation, and the comparison with other allocations. Chapter 5 provides the optimal strategies under fixed allocation with multiple retailers and the impacts of fixed proportions. Chapter 6 illustrates how to achieve supply chain coordination through capacity reservation contract and its comparison with the quantity flexibility contract, and in Chapter 7 we describe outsourcing decisions and order policies in different systems with some numerical studies. We sincerely hope that this book can provide some useful suggestions and inspirations for scholars around the world who have the same interests in this field.

Because it deals with sustainably supplying cities and reducing congestion and pollution related to goods transport in urban areas, city logistics is an important field in transportation sciences. These logistics systems need to be sustainable and reliable to ensure the continued flow of goods. Logistics and Transport Modeling in Urban Goods Movement is a pivotal reference source that provides vital research on the main approaches and techniques used in urban goods transport modelling while addressing planning and management issues. Highlighting topics such as urban logistics, vehicle routing, and greenhouse emissions, this book is ideally designed for civil/transport engineers, planners, transport economists, geographers, computer scientists, practitioners, professionals, researchers, and students seeking current research on urban goods modelling.

Foresight is an area within Futures Studies that focuses on critical thinking concerning long term developments, whether within the public sector or in industry and management, and is something of a sub-section of complexity and network science. This book examines developments in foresight methodologies and relates in its greater part to the work done in the context of the COSTA22 network of the EU on Foresight Methodologies. Foresight is a professional practice that supports significant decisions, and as such it needs to be more assured of its claims to knowledge (methodology). Foresight is practiced across many domains and is not the preserve of specialized futurists, or indeed of foresight specialists. However, the disciplines of foresight are not well articulated or disseminated across domains, leading to re-inventions and practice that does not make best use of experience in other domains.

The methodological development of foresight is an important task that aims at strengthening the pool of the tools available for application, thereby empowering the actors involved in foresight practice. Elaborating further on methodological issues, such as those presented in the present book, enables the actors involved in foresight to begin to critique current practice from this perspective and, thirdly, to begin to design foresight practice. The present trends towards methodological concerns indicates a move from given expert-predicted futures to one in which futures are nurtured through a dialogue among stakeholders. The book has four parts, each elaborating on a set of aspects of foresight methodologies. After an introductory section, Part II considers theorizing about foresight methodologies. Part III covers system content issues, and Part IV presents foresight tools and approaches."

Handbook of Mobility Data Mining, Volume Two: Mobility Analytics and Prediction introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book introduces how to design MDM platforms that adapt to the evolving mobility environment and new types of transportation and users. This helpful guide provides a basis for how to simulate and predict mobility data. After an introductory theory chapter, the book then covers crucial topics such as long-term mobility pattern analytics, mobility data generators, user information inference, Grid-based population density prediction, and more. The book concludes with a chapter on graph-based mobility data analytics. The information in this work is crucial for researchers, engineers, operators, company administrators, and policymakers in related fields, to comprehensively understand current technologies' infra-knowledge structure and limitations.

Handbook of Mobility Data Mining, Volume One: Data Preprocessing and Visualization introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book contains crucial information for researchers, engineers, operators, administrators, and policymakers seeking greater understanding of current technologies' infra-knowledge structure and limitations. Further, the book introduces how to design MDM platforms that adapt to the evolving mobility environment, new types of transportation, and users based on an integrated solution that utilizes sensing and communication capabilities to tackle significant challenges faced by the MDM field. This volume focuses on how to efficiently pre-process mobile big data to extract and utilize critical feature information of high-dimensional city people flow. The book first provides a conceptual theory and framework, then discusses data sources, trajectory map-matching, noise filtering, trajectory data segmentation, data quality assessment, and more, concluding with a chapter on privacy protection in mobile big data mining.

This book focuses on negotiation processes and how negotiation modeling frameworks and information technology can support these. A modeling framework for negotiation as a purposeful complex adaptive process is presented and computer-implemented in the first three chapters. Two game-theoretic contributions use non-cooperative games in extensive form and a computer-implemented graph model for conflict resolution, respectively. Two chapters use the negotiators' joint utility distribution to provide problem structure and computer support. A chapter on cognitive support uses restructurable modeling as a framework. One chapter matches information technologies with negotiation tasks. Another develops computer support based on preference programming. Two final chapters develop a stakeholder approach to support system evaluation, and a research framework for them, respectively. Negotiation Processes: Modeling Frameworks and Information Technology will be of interest to researchers and students in the areas of negotiation, group decision/negotiation support systems and management science, as well as to practising negotiators interested in this technology.

This book provides a comprehensive overview of recent developments in network dynamics and control with applications to supply chains, manufacturing and logistics systems. It systemizes these developments in the form of new taxonomies and methodological principles to shape the research domain of supply network dynamics control. Uniquely, the book links the fundamentals of control and system theories and artificial intelligence with supply chain and operations management. It addresses the needs of researchers and practitioners alike, revealing the challenges and opportunities of supply chain and operations management by means of dynamic system analysis.

This book gathers selected peer-reviewed papers from the 15th World Congress on Engineering Asset Management (WCEAM), which was hosted by The Federal University of Mato Grosso do Sul Campo Grande, Brazil, from 15--18 August 2021 This book covers a wide range of topics in engineering asset management, including: strategy and standards; sustainability and resiliency; servitisation and Industry 4.0 business models; asset information systems; and asset management decision-making. The breadth and depth of these state-of-the-art, comprehensive proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students.