This volume, Systems and Management Science by Extremal Methods, is the second in a series dedicated to honoring and extending the work of Abraham Charnes. The first volume, entitled Extremal Methods and Systems Analysis (Springer Verlag, Berlin, 1980), was edited by A.V. Fiacco and K.O. Kortanek. Subtitled "An International Symposium on the Occasion of Abraham Charnes' Sixtieth Birthday," this first volume consisted of a selection from papers presented at a conference in honor of Professor Charnes held at The University of Texas at Austin in September 1977. This second volume consists of papers, to be described more fully below, that were presented in a similar 2 conference held at the IC Institute of The University of Texas at Austin, Texas, in October of 1987, to honor Dr. Charnes on his seventieth birthday. All these papers were written by scholars and scientists whose own work has been affected by the contributions of this distinguished scholar and educator over a long period of time.

This proceedings volume presents new methods and applications in Operational Research and Management Science with a special focus on Business Analytics. Featuring selected contributions from the XIV Balkan Conference on Operational Research held in Thessaloniki, Greece in 2020 (BALCOR 2020), it addresses applications and methodological tools or techniques in various areas of Operational Research, such as agent-based modelling, big data and business analytics, data envelopment analysis, data mining, decision support systems, fuzzy systems, game theory, heuristics, metaheuristics and nature inspired optimization algorithms, linear and nonlinear programming, machine learning, multiple criteria decision analysis, network design and optimization, queuing theory, simulation and statistics.

This book is devoted to presenting theoretical fundamentals for the methods of multiple criteria decision making (MCDM) in the social sciences with particular intent to their applicability to real-world decision making. The main characteristics of the complex problems facing humans in the world today are multidimensional and have multiple objecti ves; they are large-scale, and have nonconimensura te and conflicting objectives, such as economic, environmental, societal, technical, and aesthetic ones. The authors intend to establish basic concepts for treating these complex problems and to present methodological discussions for MCDM with some applications to administrative, or regional, planning. MCDM is composed of two phases: analytical and judgmental. In this book, we intend to consolidate these two phases and to present integrated methodologies for manipulating them with particular interest in managerial decision making, which has not yet been properly treated in spite of its urgent necessi ty. Al though a number of books in MCDM fields have already been published in recent years, most of them have mainly trea ted one aspect of MCDM. Our work specifically intends to trea t the methodology in unified systems and to construct a conceptual structure with special regards to the intrinsic properties of MCDM and its "economic meanings" from the social scientific point of view.

This indispensable text offers students a high quality treatment of strategic operations management. It provides the reader with a clear understanding of the importance and nature of operations strategy by determining exactly which management activities, core competencies, resources and technologies underpin an operational strategy. The book demonstrates how various operational elements and components can be combined and customised into unique operational strategies. When these strategies are correctly implemented, they provide sustainable competitive advantage and allow firms to provide a diverse range of services and goods in their increasingly demanding, complex and dynamic marketplaces and spaces.
Includes chapters covering customising operational strategies for retail, manufacturing, services and SMEs, and sections on eBusiness and complexity theory in relation to operations theory.
Features include:
*extended case-studies including several from Europe and the USA
*case vignettes
*learning objectives
*key terms
*chapter introduction and 'maps' to aid reader accessibility
*'time out' boxes to prompt the reader to reflect on what has been learnt
*'critical reflection' boxes that analyse theories and models.

Related link: www.routledge.com/textbooks/0415256542
eBook available with sample pages: 0203361520

"Optimization on Metric and Normed Spaces" is devoted to the recent progress in optimization on Banach spaces and complete metric spaces. Optimization problems are usually considered on metric spaces satisfying certain compactness assumptions which guarantee the existence of solutions and convergence of algorithms. This book considers spaces that do not satisfy such compactness assumptions. In order to overcome these difficulties, the book uses the Baire category approach and considers approximate solutions. Therefore, it presents a number of new results concerning penalty methods in constrained optimization, existence of solutions in parametric optimization, well-posedness of vector minimization problems, and many other results obtained in the last ten years. The book is intended for mathematicians interested in optimization and applied functional analysis.

This volume reflects the theme of the INFORMS 2004 Meeting in Denver: Back to OR Roots. Emerging as a quantitative approach to problem-solving in World War II, our founders were physicists, mathematicians, and engineers who quickly found peace-time uses. It is fair to say that Operations Research (OR) was born in the same incubator as computer science, and it has spawned many new disciplines, such as systems engineering, health care management, and transportation science. Although people from many disciplines routinely use OR methods, many scientific researchers, engineers, and others do not understand basic OR tools and how they can help them. Disciplines ranging from finance to bioengineering are the beneficiaries of what we do - we take an interdisciplinary approach to problem-solving. Our strengths are modeling, analysis, and algorithm design. We provide a quanti- tive foundation for a broad spectrum of problems, from economics to medicine, from environmental control to sports, from e-commerce to computational - ometry. We are both producers and consumers because the mainstream of OR is in the interfaces. As part of this effort to recognize and extend OR roots in future probl- solving, we organized a set of tutorials designed for people who heard of the topic and want to decide whether to learn it. The 90 minutes was spent addre- ing the questions: What is this about, in a nutshell? Why is it important? Where can I learn more? In total, we had 14 tutorials, and eight of them are published here.

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

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 tackles issues associated with inconsistency in pairwise comparisons from both theoretical and practical perspectives. Human judgments are seldom absolutely consistent, or absolutely precise, therefore problems of measuring and handling inconsistency belong among hot topics of the current research, especially in the theoretical framework of multiple criteria decision aiding (MCDA). The book presents and discusses the state-of-the-art of this field including both cardinal and ordinal inconsistency, the problems of different scales for comparisons and inconsistency reduction, and the alternative approaches to inconsistency detection and measurement. This book is a unique one-stop guide for readers who are interested in inconsistency in pairwise comparisons. Researchers and practitioners in the area of multiple-criteria decision-making (MCDM) and the analytic hierarchy process (AHP) will find this informative book particularly valuable.  

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 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."

This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems. The list of topics covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.

Contains case studies from engineering and operations research

Includes commented literature for each chapter

A smart city is a city that collates data via various technological methods, and uses insights gleaned from this data to manage assets, resources, services and operations more efficiently. Though the concept of 'smart cities' is fairly new, there is a vast amount of interest in the topic, exploring how technological advances can be used to better manage the integration of business and operations within a city, as well as how sustainable choices can be written into the fabric of an urban space. This book explores logistics within smart cities: the greater logistical demands of a smart city, how logistics can be adapted to new challenges, and what sort of new logistical support a smart city will need. The book pays particular attention to how logistical innovation within a smart city can lead to greater sustainability in the city, and on a global level. It will be of interest to academics working in logistics, urban planning, innovation management, digital technology, sustainability management, and operations management.

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.

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.

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."

The proliferation of new products has become a common phenomenon in today's business world. Most companies now offer hundreds, if not thousands, of stock keeping units (SKUs) in order to compete in the market place. Companies that expand their product and service varieties now face a new set of problems: accurate demand forecasts, controlling production and inventory costs, and providing high quality delivery performance. In addition, marketing managers will often advocate widening product lines for increasing revenue and market share, but increasing product lines can also decrease the efficiency of manufacturing processes and distribution systems. Hence, firms must weigh the benefits of increasing product variety against its cost and determine the optimal level of product variety to offer to their customers. Product Variety Management examines the interrelated problems between the marketing and production functions in industry, and through a series of research survey papers by leading scholars in economics, engineering, marketing, and operations research, the book addresses the following questions: Why do companies extend their product lines? Do consumers care about product variety? Will a brand with more variety enjoy higher market share? How should product variety be measured? How can a company exploit its product and process design to deliver a higher level of product variety quickly and cheaply? What should the level of product variety be and what should the price of each of the product variants be? What kind of challenges would a company face in offering a high level of product variety and how can these obstacles be overcome? The solutions to these questions are drawn frommultiple functions and a variety of disciplines. Product Variety Management is a state-of-the-art treatment of a multi-disciplinary approach to product variety.

This book focuses on research methodologies that apply to business research, particularly for researchers and managers embarking thereon to support managerial decision-making in the industry. In doing so, the book's objective is to guide business researchers in identifying, defining, and applying rigorous academic methodologies that will enable them to formulate, design, and execute effective research that answers their specific management problems. Such guidance can empower organizational managers to understand that business research can contribute to practical solutions to actual problems experienced in the industry. In addition, by emphasizing the integrative nature between (1) academic research and (2) experienced industry problems, it becomes possible to foster an awareness of such research's potential impact on organizational performance management, sustainability, and resilience. With that, attention is given to narrowing the gap between theory and practice, which requires that fundamentals of scientific research be adhered to while maintaining the delicate balance between a practice-friendly guide to pragmatically sound and academically rigorous business research.

This book provides insights from research and practice in how organizations were able to sustain resilience in their global supply chains during the COVID-19 pandemic and to advance the understanding of supply chain risk management. The chapters highlight the lessons learned, insist on new models for resilience, suggest improved supply chain risk methodologies and bridge the gap between research and practice. It helps readers acquire greater knowledge, strategic approaches, new methods, and practical tools for ensuring global supply chain resilience.

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.

1 Nabil R. Adam and Ali Dogramaci Measuring, analyzing, and improving productivity in a given organization is a complex process that involves the contributions of economists, industrial engineers, operations researchers, management scientists, and lawyers. The objective of this book is to provide the reader with a sample of original papers that relate to these productivity topics at the organizational level. In the book, the word organization refers to business firms and municipal organizations. The hook is divided into three parts: perspectives on productivity mea surement, a range of studies at the micro level, and some productivity issues in public organizations. Part I, which consists of three chapters, deals with productivity measurement. The first two chapters of this part cover a broad framework of measurement concepts and techniques; the last chapter, on the other hand, provides the reader with an example of productivity measurement for a specific industry (in this case, food retail ing). Thus, a spectrum of productivity measurement issues is covered in this part of the book."

This book introduces readers to a new approach to identifying stock market bubbles by using the illiquidity premium, a parameter derived by employing conic finance theory. Further, it shows how to develop the closed form formulas of the bid and ask prices of European options by using Black-Scholes and Kou models. By using the derived formulas and sliding windows technique, the book explains how to numerically calculate illiquidity premiums. The methods introduced here will enable readers interested in risk management, portfolio optimization and hedging in real-time to identify when asset prices are in a bubble state and when that bubble bursts. Moreover, the techniques discussed will allow them to accurately recognize periods of exuberance and panic, and to measure how different strategies work during these phases with respect to calmer periods of market behavior. A brief history of financial bubbles and an outlook on future developments serve to round out the coverage.