Why do people in a business negotiation settle for less than each of them could and should receive? Two rational players face off in an economic game. Each pursues interests as conventional theory dictates, but all too often, the result is suboptimal. Why do they fail to capture what Dr. Young calls the cooperative surplus? Dr. Young proposes that the root of the problem lies in the philosophical assumptions underlying decision and game theory. The common understanding of economic rationality is fundamentally flawed, he says. It assumes that rational players are always self-interested and that they will make decisions on the basis of consequences. Arguing that no theory of economic rationality developed from this foundation can lead to the desired prescriptive results, Dr. Young maintains that a successful prescriptive theory of rationality must start from a different premise: the notion of actors as autonomous agents who act over and above their inclinations to express their identity.

Dr. Young advances his own notion of economic rationality, then seeks to establish rules by which rational economic players can jointly create a common base for business negotiation. The results of bargaining will then be in equilibrium, and a solution optimal to both sides can be reached. Already praised by philosophers in Europe for its innovative vision and practicality, this book is a must for business executives and attorneys engaged in business negotiations, as well as for their colleagues with similar interests in the academic community.

Using numerical examples to illustrate their concepts and results, this book examines recently developed fuzzy multi-criteria methods, such as Intuitionistic Fuzzy TOPSIS, Intuitionistic Fuzzy TOPSIS & DEA-AHP, Intuitionistic VIKOR, Pythagorean WASPAS, Pythagorean ENTROPI, Hesitant CBD, Hesitant MABAC, Triangular EDAS, Triangular PROMETHEE, q-Rung Orthopair COPRAS, and Fuzzy Type - 2 ELECTRE. Each chapter covers practical applications in addition to fresh developments and results. Given its structure and scope, the book can be used as a textbook in graduate courses on operations research and industrial engineering. It also offers a valuable resource for scientists working in a range of disciplines that require multi-criteria decision making.

Are people ever rational? Consider this: You auction off a one-dollar bill to the highest bidder, but you set the rules so that the second highest bidder also has to pay the amount of his last bid, even though he gets nothing. Would people ever enter such an auction? Not only do they, but according to Martin Shubik, the game's inventor, the average winning bid (for a dollar, remember) is $3.40. Many winners report that they bid so high only because their opponent "went completely crazy." This game lies at the intersection of three subjects of eternal fascination: human psychology, morality, and John von Neumann's game theory. Hungarian game-theorist Laszlo Mero introduces us to the basics of game theory, including such concepts as zero-sum games, Prisoner's Dilemma and the origins of altruism; shows how game theory is applicable to fields ranging from physics to politics; and explores the role of rational thinking in the context of many different kinds of thinking. This fascinating, urbane book will interest everyone who wonders what mathematics can tell us about the human condition.

This book addresses and disseminates state-of-the-art research and development of differential evolution (DE) and its recent advances, such as the development of adaptive, self-adaptive and hybrid techniques. Differential evolution is a population-based meta-heuristic technique for global optimization capable of handling non-differentiable, non-linear and multi-modal objective functions. Many advances have been made recently in differential evolution, from theory to applications. This book comprises contributions which include theoretical developments in DE, performance comparisons of DE, hybrid DE approaches, parallel and distributed DE for multi-objective optimization, software implementations, and real-world applications. The book is useful for researchers, practitioners, and students in disciplines such as optimization, heuristics, operations research and natural computing.

In the last decades, algorithmic advances as well as hardware and software improvements have provided an excellent environment to create and develop solving methods to hard optimization problems. Modern exact and heuristic techniques are dramatically enhancing our ability to solve significant practical problems. This monograph sets out state-of-the-art methodologies for solving combinatorial optimization problems, illustrating them with two well-known problems. This second edition of the book extends the first one by adding to the 'linear ordering problem' (LOP), included in the first edition, the 'maximum diversity problem' (MDP). In this way, we provide the reader with the background, elements and strategies to tackle a wide range of different combinatorial optimization problems. The exact and heuristic techniques outlined in these pages can be put to use in any number of combinatorial optimization problems. While the authors employ the LOP and the MDP to illustrate cutting-edge optimization technologies, the book is also a tutorial on how to design effective and successful implementations of exact and heuristic procedures alike. This monograph provides the basic principles and fundamental ideas that will enable students and practitioners to create valuable applications based on both exact and heuristic technologies. Specifically, it is aimed at engineers, scientists, operations researchers, and other applications specialists who are looking for the most appropriate and recent optimization tools to solve particular problems. The book provides a broad spectrum of advances in search strategies with a focus on its algorithmic and computational aspects.

Insurance Economics brings together the economic analysis of decision making under risk, risk management and demand for insurance among individuals and corporations, objectives pursued and management tools used by insurance companies, the regulation of insurance, and the division of labor between private and social insurance. Appropriate both for advanced undergraduate and graduate students of economics, management, and finance, this text provides the background required to understand current research. Predictions derived from theoretical arguments are not merely stated, but also related to empirical evidence. Throughout the book, conclusions summarize key results, helping readers to check their knowledge and comprehension. Issues discussed include paradoxes in decision making under risk and attempts at their resolution, moral hazard and adverse selection including the possibility of a "death spiral", and future challenges to both private and social insurance such as globalization and the availability of genetic information. This second edition has been extensively revised. Most importantly, substantial content has been added to represent the evolution of risk-related research. A new chapter, Insurance Demand II: Nontraditional Approaches, provides a timely addition in view of recent developments in risk theory and insurance. Previous discussions of Enterprise Risk Management, long-term care insurance, adverse selection, and moral hazard have all been updated. In an effort to expand the global reach of the text, evidence and research from the U.S. and China have also been added.

Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.

This book features mathematical and formal philosophers' efforts to understand philosophical questions using mathematical techniques. It offers a collection of works from leading researchers in the area, who discuss some of the most fascinating ways formal methods are now being applied. It covers topics such as: the uses of probable and statistical reasoning, rational choice theory, reasoning in the environmental sciences, reasoning about laws and changes of rules, and reasoning about collective decision procedures as well as about action. Utilizing mathematical techniques has been very fruitful in the traditional domains of formal philosophy - logic, philosophy of mathematics and metaphysics - while formal philosophy is simultaneously branching out into other areas in philosophy and the social sciences. These areas particularly include ethics, political science, and the methodology of the natural and social sciences. Reasoning about legal rules, collective decision-making procedures, and rational choices are of interest to all those engaged in legal theory, political science and economics. Statistical reasoning is also of interest to political scientists and economists.

Maximizing reader insights into the roles of intelligent agents in networks, air traffic and emergency departments, this volume focuses on congestion in systems where safety and security are at stake, devoting special attention to applying game theoretic analysis of congestion to: protocols in wired and wireless networks; power generation, air transportation and emergency department overcrowding. Reviewing exhaustively the key recent research into the interactions between game theory, excessive crowding, and safety and security elements, this book establishes a new research angle by illustrating linkages between the different research approaches and serves to lay the foundations for subsequent analysis. Congestion (excessive crowding) is defined in this work as all kinds of flows; e.g., road/sea/air traffic, people, data, information, water, electricity, and organisms. Analysing systems where congestion occurs - which may be in parallel, series, interlinked, or interdependent, with flows one way or both ways - this book puts forward new congestion models, breaking new ground by introducing game theory and safety/security into proceedings. Addressing the multiple actors who may hold different concerns regarding system reliability; e.g. one or several terrorists, a government, various local or regional government agencies, or others with stakes for or against system reliability, this book describes how governments and authorities may have the tools to handle congestion, but that these tools need to be improved whilst additionally ensuring safety and security against various threats. This game-theoretic analysis sets this two volume book apart from the current congestion literature and ensures that the work will be of use to postgraduates, researchers, 3rd/4th-year undergraduates, policy makers, and practitioners.

This book introduces the advances in synchromodal logistics and provides a framework to classify various optimisation problems in this field. It explores the application of this framework to solve a broad range of problems, such as problems with and without a central decision-maker, problems with and without full information, deterministic problems, problems coping with uncertainty, optimisation of a full network design problem. It covers theoretical constructs, such as discrete optimisation, robust optimisation, optimisation under uncertainty, multi-objective optimisation and agent based equilibrium models. Moreover, practical elaborated use cases are presented to deepen understanding. The book gives both researchers and practitioners a good overview of the field of synchromodal optimisation problems and offers the reader practical methods for modelling and problem-solving.

This book deals with several types of multi-dimensional control problems in the face of data uncertainty for vector cases-multi-dimensional multi-objective control problem with uncertain objective functionals, uncertain constraint functionals, and uncertain objective as well as constraint functionals, uncertain multi-dimensional multi-objective control problem with semi-infinite constraints, uncertain dual multi-dimensional multi-objective variational control problem, and second-order PDE&PDI constrained robust optimization problem. The book provides the solution approaches-an exact l1 penalty function approach, modified objective approach, robust approach-in the simplest way to solve the recent developing optimization problems in the sense of uncertainty.

This book focuses primarily on the nature-inspired approach for designing smart applications. It includes several implementation paradigms such as design and path planning of wireless network, security mechanism and implementation for dynamic as well as static nodes, learning method of cloud computing, data exploration and management, data analysis and optimization, decision taking in conflicting environment, etc. The book fundamentally highlights the recent research advancements in the field of engineering and science.

This volume presents state-of-the-art complementarity applications, algorithms, extensions and theory in the form of eighteen papers. These at the International Conference on Com invited papers were presented plementarity 99 (ICCP99) held in Madison, Wisconsin during June 9-12, 1999 with support from the National Science Foundation under Grant DMS-9970102. Complementarity is becoming more widely used in a variety of appli cation areas. In this volume, there are papers studying the impact of complementarity in such diverse fields as deregulation of electricity mar kets, engineering mechanics, optimal control and asset pricing. Further more, application of complementarity and optimization ideas to related problems in the burgeoning fields of machine learning and data mining are also covered in a series of three articles. In order to effectively process the complementarity problems that arise in such applications, various algorithmic, theoretical and computational extensions are covered in this volume. Nonsmooth analysis has an im portant role to play in this area as can be seen from articles using these tools to develop Newton and path following methods for constrained nonlinear systems and complementarity problems. Convergence issues are covered in the context of active set methods, global algorithms for pseudomonotone variational inequalities, successive convex relaxation and proximal point algorithms. Theoretical contributions to the connectedness of solution sets and constraint qualifications in the growing area of mathematical programs with equilibrium constraints are also presented. A relaxation approach is given for solving such problems. Finally, computational issues related to preprocessing mixed complementarity problems are addressed."

This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study. Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field. T. J. Sullivan was Warwick Zeeman Lecturer at the Mathematics Institute of the University of Warwick, United Kingdom, from 2012 to 2015. Since 2015, he is Junior Professor of Applied Mathematics at the Free University of Berlin, Germany, with specialism in Uncertainty and Risk Quantification.

This first book focuses on uncertain graph and network optimization. It covers three different main contents: uncertain graph, uncertain programming and uncertain network optimization. It also presents applications of uncertain network optimization in a lot of real problems such as transportation problems, dispatching medical supplies problems and location problems. The book is suitable for researchers, engineers, teachers and students in the field of mathematics, information science, computer science, decision science, management science and engineering, artificial intelligence, industrial engineering, economics and operations research.

"Game Theory for Economists" introduces economists to the game-theoretic approach of modelling economic behaviour and interaction, focusing on concepts and ideas from the vast field of game-theoretic models which find commonly used applications in economics. This careful selection of topics allows the reader to concentrate on the parts of the game which are the most relevant for the economist who does not want to become a specialist. Written at a level appropriate for a student or researcher with a solid microeconomic background, the book should provide the reader with skills necessary to formalize economic games and to make them accessible for game theoretic analysis. It offers a concise introduction to game theory which provides economists with the techniques and results necessary to follow the literature in economic theory; helps the reader formalize economic problems; and, concentrates on equilibrium concepts that are most commonly used in economics.

This book offers a comprehensive overview of the financial systems of major industrialized countries using the statistical framework of the financial accounts. After a discussion of how economists agreed to create a framework to monitor the financial linkages between surplus and deficit sectors, the book analyzes in detail the composition and the recent evolution of financial assets and liabilities for households (including public pension rights), firms and intermediaries. Next, the volume studies the convergence patterns of financial structures and their influence on the effectiveness of monetary policy within European countries. The final chapter unifies the previous pictures, showing how the effects of financial integration and global imbalances could have been foreseen based on the financial accounts. The analysis and information contained in the book will help the readers to understand many issues and challenges raised by the recent financial crisis.

Written by a leading expert in turnpike phenomenon, this book is devoted to the study of symmetric optimization, variational and optimal control problems in infinite dimensional spaces and turnpike properties of their approximate solutions. The book presents a systematic and comprehensive study of general classes of problems in optimization, calculus of variations, and optimal control with symmetric structures from the viewpoint of the turnpike phenomenon. The author establishes generic existence and well-posedness results for optimization problems and individual (not generic) turnpike results for variational and optimal control problems. Rich in impressive theoretical results, the author presents applications to crystallography and discrete dispersive dynamical systems which have prototypes in economic growth theory. This book will be useful for researchers interested in optimal control, calculus of variations turnpike theory and their applications, such as mathematicians, mathematical economists, and researchers in crystallography, to name just a few.

This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is on orthogonal kernel functions, and the properties of the classical kernel functions-Chebyshev, Legendre, Gegenbauer, and Jacobi-are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations. On the other hand, nowadays, the real-time and big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms based on orthogonal kernel functions in different situations and gives a significant perspective to all machine learning and scientific machine learning researchers all around the world to utilize fractional orthogonal kernel functions in their pattern recognition or scientific computing problems.

This book defines and studies a combinatorial object called the pedigree and develops the theory for optimising a linear function over the convex hull of pedigrees (the Pedigree polytope). A strongly polynomial algorithm implementing the framework given in the book for checking membership in the pedigree polytope is a major contribution. This book challenges the popularly held belief in computer science that a problem included in the NP-complete class may not have a polynomial algorithm to solve. By showing STSP has a polynomial algorithm, this book settles the P vs NP question. This book has illustrative examples, figures, and easily accessible proofs for showing this unexpected result. This book introduces novel constructions and ideas previously not used in the literature. Another interesting feature of this book is it uses basic max-flow and linear multicommodity flow algorithms and concepts in these proofs establishing efficient membership checking for the pedigree polytope. Chapters 3-7 can be adopted to give a course on Efficient Combinatorial Optimization. This book is the culmination of the author's research that started in 1982 through a presentation on a new formulation of STSP at the XIth International Symposium on Mathematical Programming at Bonn.

The primary aim of this book is to present notions of convex analysis which constitute the basic underlying structure of argumentation in economic theory and which are common to optimization problems encountered in many applications. The intended readers are graduate students, and specialists of mathematical programming whose research fields are applied mathematics and economics. The text consists of a systematic development in eight chapters, with guided exercises containing sometimes significant and useful additional results. The book is appropriate as a class text, or for self-study.

In trying to make a satisfactory decision when imprecise and multicriteria situations are involved, a decision maker has to use a fuzzy multicriteria decision making method. "Fuzzy Multi-Criteria Decision Making" (MCDM) presents fuzzy multiattribute and multiobjective decision-making methodologies by distinguished MCDM researchers.

In summarizing the concepts and results of the most popular fuzzy multicriteria methods, using numerical examples, this work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results.

This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.

This book describes concepts and tools needed for water resources management, including methods for modeling, simulation, optimization, big data analysis, data mining, remote sensing, geographical information system, game theory, conflict resolution, System dynamics, agent-based models, multiobjective, multicriteria, and multiattribute decision making and risk and uncertainty analysis, for better and sustainable management of water resources and consumption, thus mitigating the present and future global water shortage crisis. It presents the applications of these tools through case studies which demonstrate its benefits of proper management of water resources systems. This book acts as a reference for students, professors, industrial practitioners, and stakeholders in the field of water resources and hydrology.

This book presents mathematical models of demand-side management programs, together with operational and control problems for power and renewable energy systems. It reflects the need for optimal operation and control of today's electricity grid at both the supply and demand spectrum of the grid. This need is further compounded by the advent of smart grids, which has led to increased customer/consumer participation in power and renewable energy system operations. The book begins by giving an overview of power and renewable energy systems, demand-side management programs and algebraic modeling languages. The overview includes detailed consideration of appliance scheduling algorithms, price elasticity matrices and demand response incentives. Furthermore, the book presents various power system operational and control mathematical formulations, incorporating demand-side management programs. The mathematical formulations developed are modeled and solved using the Advanced Interactive Multidimensional Modeling System (AIMMS) software, which offers a powerful yet simple algebraic modeling language for solving optimization problems. The book is extremely useful for all power system operators and planners who are concerned with optimal operational procedures for managing today's complex grids, a context in which customers are active participants and can curb/control their demand. The book details how AIMMS can be a useful tool in optimizing power grids and also offers a valuable research aid for students and academics alike.

The COVID-19 pandemic has vividly and dramatically demonstrated the importance of supply chains to the functioning of societies and our economies. The discussion in this timely book explores prominent issues concerning supply chain networks and labor. The readership is aimed to include students, researchers, practitioners, and policy-makers, interested in the wide range of topics presented in these pages. Labor has a particular focus as the driver behind supply chains, whether associated with food products, life-saving medicines and supplies, or high tech products that make innovation possible, just to name a few. The impacts of policy interventions, in the form of wage bounds, and their ramifications, in terms of volume of attracted labor, product prices, product volumes, as well as profits, are explored. Profit-maximizing firms are considered (with relevant associated issues such as waste management in the case of the food sector, for example), but also non-profits, as in blood services, as well as humanitarian organizations engaged in disaster relief. The book is filled with many network figures, graphs, and tables with data, both input and output and includes an appendix that provides the foundations of the underlying mathematical methodologies used. The book offers strong evidence for the need to provide a holistic, system-wide perspective for the modeling, analysis, and solution of supply chain problems with the inclusion of the critical labor resources. A formalism using the prism of supply chain networks, which yields a graphic representation of supply chains, consisting of multiple stakeholders, is constructed. Models that capture the behaviors and interactions of single decision-makers as well as multiple decision-makers engaged in supply chain activities of production, transportation, storage, and distribution, are considered. The models capture many realistic constraints faced by firms today, as they seek to produce and deliver products, while dealing with competition, various constraints on labor, a variety of disruptions, labor shortages, challenges associated with proper wage-determination, plus the computation of optimal investments in labor productivity subject to budget constraints. The book provides prescriptive suggestions in terms of how to ameliorate negative impacts of labor disruptions and demonstrate benefits of appropriate wage determination.