In mathematical modeling of processes one often encounters optimization problems involving more than one objective function, so that Multiobjective Optimization (or Vector Optimization) has received new impetus. The growing interest in multiobjective problems, both from the theoretical point of view and as it concerns applications to real problems, asks for a general scheme which embraces several existing developments and stimulates new ones. In this book the authors provide the newest results and applications of this quickly growing field. This book will be of interest to graduate students in mathematics, economics, and engineering, as well as researchers in pure and applied mathematics, economics, engineering, geography, and town planning. A sound knowledge of linear algebra and introductory real analysis should provide readers with sufficient background for this book.

This book considers problems of optimization arising in the design of electromagnetic radiators and receivers. The authors develop a systematic general theory that can be applied to a wide class of structures. The theory is illustrated with familiar, simple examples and indications of how the results can be applied to more complicated structures. The final chapter introduces techniques from multicriteria optimization in antenna design. The material is intended for a dual audience of mathematicians and mathematically-sophisticated engineers. References to both the mathematics and engineering literature help guide the reader through the necessary mathematical background.

Building on the pioneering work by the Nobel Memorial Laureate, John Nash, Professor Thomson has brought together a broad selection of seminal articles which analyse and discuss bargaining and the theory of cooperative games. Beginning with a distinguished collection of papers discussing the origins of game theory, this volume systematically explores its development as a tool to illuminate economic behaviour. It includes the work of highly accomplished academics whose discoveries over the years have shaped the direction of this subject. With his insightful introduction, the editor has ensured that this indispensable book is suitable for anyone with an interest in cooperative gaming.

This book continues the biannual series of conference proceedings, which has become a classical reference resource in traffic and granular research alike, and addresses the latest developments at the intersection of physics, engineering and computational science. These involve complex systems, in which multiple simple agents, be they vehicles or particles, give rise to surprising and fascinating phenomena. The contributions collected in these proceedings cover several research fields, all of which deal with transport. Topics include highway, pedestrian and internet traffic; granular matter; biological transport; transport networks; data acquisition; data analysis and technological applications. Different perspectives, i.e., modeling, simulations, experiments, and phenomenological observations are considered.

The aim of this volume is to show how Fuzzy Sets and Systems can help to provide robust and adaptive heuristic optimization algorithms in a variety of situations. The book presents the state of the art and gives a broad overview on the real practical applications that Fuzzy Sets, based on heuristic algorithms, have.

This special volume is dedicated to Boris M. Mordukhovich, on the occasion of his 60th birthday, and aims to celebrate his fundamental contributionsto variational analysis, generalizeddifferentiationand their applications.A main exampleof these contributions is Boris' recent opus magnus "Variational Analysis and Generalized Differentiation"(vols. I and II) [2,3]. A detailed explanationand careful description of Boris' research and achievements can be found in [1]. Boris' active work and jovial attitude have constantly inspired researchers of several generations, with whom he has generously shared his knowledgeand ent- siasm, along with his well-known warmth and human touch. Variationalanalysis is a rapidlygrowing?eld within pure and applied mathem- ics, with numerous applications to optimization, control theory, economics, en- neering, and other disciplines. Each of the 12 chapters of this volume is a carefully reviewed paper in the ?eld of variational analysis and related topics. Many chapters of this volume were presented at the International Symposium on Variational Analysis and Optimization (ISVAO), held in the Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan, from November 28 to November 30, 2008. The symposium was organized in honour of Boris' 60thbirthday.It broughttogetherBorisandotherresearchersto discusssta- of-the-art results in variational analysis and its applications, with emphasis on op- mization and control. We thank the organizers and participants of the symposium, who made the symposium a highly bene?cial and enjoyable event. We are also grateful to all the authors of this special volume, who have taken the opportunityto celebrate Boris' birthdayand his decadesof contributionsto the area.

The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems.
In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods.

The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest.

Review of First Edition:

"The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make'Introduction to Stochastic Programming' an ideal textbook for the area." (Interfaces, 1998)

"

Starting with a simple formulation accessible to all mathematicians, this second edition is designed to provide a thorough introduction to nonstandard analysis. Nonstandard analysis is now a well-developed, powerful instrument for solving open problems in almost all disciplines of mathematics; it is often used as a 'secret weapon' by those who know the technique. This book illuminates the subject with some of the most striking applications in analysis, topology, functional analysis, probability and stochastic analysis, as well as applications in economics and combinatorial number theory. The first chapter is designed to facilitate the beginner in learning this technique by starting with calculus and basic real analysis. The second chapter provides the reader with the most important tools of nonstandard analysis: the transfer principle, Keisler's internal definition principle, the spill-over principle, and saturation. The remaining chapters of the book study different fields for applications; each begins with a gentle introduction before then exploring solutions to open problems. All chapters within this second edition have been reworked and updated, with several completely new chapters on compactifications and number theory. Nonstandard Analysis for the Working Mathematician will be accessible to both experts and non-experts, and will ultimately provide many new and helpful insights into the enterprise of mathematics.

Optimization in Computational Chemistry and Molecular Biology: Local and Global Approaches covers recent developments in optimization techniques for addressing several computational chemistry and biology problems. A tantalizing problem that cuts across the fields of computational chemistry, biology, medicine, engineering and applied mathematics is how proteins fold. Global and local optimization provide a systematic framework of conformational searches for the prediction of three-dimensional protein structures that represent the global minimum free energy, as well as low-energy biomolecular conformations. Each contribution in the book is essentially expository in nature, but of scholarly treatment. The topics covered include advances in local and global optimization approaches for molecular dynamics and modeling, distance geometry, protein folding, molecular structure refinement, protein and drug design, and molecular and peptide docking. Audience: The book is addressed not only to researchers in mathematical programming, but to all scientists in various disciplines who use optimization methods in solving problems in computational chemistry and biology.

This book focuses on problems at the interplay between the theory of partitions and optimal transport with a view toward applications. Topics covered include problems related to stable marriages and stable partitions, multipartitions, optimal transport for measures and optimal partitions, and finally cooperative and noncooperative partitions. All concepts presented are illustrated by examples from game theory, economics, and learning.

This original new book offers a comprehensive and engaging perspective on the theory of vertical differentiation. It enables the reader to grasp the key concepts and effects that product quality has both on firms' behaviour and market structure, and the ways in which this relationship has evolved. With contributions from prominent figures in the field, the book investigates a number of important topics, such as the choice of the optimal product range, profit sharing, the existence of equilibrium in duopoly games, positional effects attached to status goods, international trade, collusion, advertising and the dynamics of capital accumulation for quality improvement and product innovation. Using both static and dynamic approaches, these aspects are assessed in relation to the manifold issues of regulation, competition policy and trade policy. Product differentiation and its influence on consumer behaviour and the performance of firms is a core topic in the existing literature in the fields of industrial organization, international trade and economic growth. This book will be an essential read for researchers, students and professional scholars working in these areas, especially those with an interest in antitrust regulation.

This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11-12, 2010 a workshop entitled 'Optimization and Data Analysis in Biomedical Informatics' was organized at The Fields Institute. Following this event invited contributions were gathered based on the talks presented at the workshop, and additional invited chapters were chosen from world's leading experts. In this publication, the authors share their expertise in the form of state-of-the-art research and review chapters, bringing together researchers from different disciplines and emphasizing the value of mathematical methods in the areas of clinical sciences. This work is targeted to applied mathematicians, computer scientists, industrial engineers, and clinical scientists who are interested in exploring emerging and fascinating interdisciplinary topics of research. It is designed to further stimulate and enhance fruitful collaborations between scientists from different disciplines.

Many questions dealing with solvability, stability and solution methods for va- ational inequalities or equilibrium, optimization and complementarity problems lead to the analysis of certain (perturbed) equations. This often requires a - formulation of the initial model being under consideration. Due to the specific of the original problem, the resulting equation is usually either not differ- tiable (even if the data of the original model are smooth), or it does not satisfy the assumptions of the classical implicit function theorem. This phenomenon is the main reason why a considerable analytical inst- ment dealing with generalized equations (i.e., with finding zeros of multivalued mappings) and nonsmooth equations (i.e., the defining functions are not c- tinuously differentiable) has been developed during the last 20 years, and that under very different viewpoints and assumptions. In this theory, the classical hypotheses of convex analysis, in particular, monotonicity and convexity, have been weakened or dropped, and the scope of possible applications seems to be quite large. Briefly, this discipline is often called nonsmooth analysis, sometimes also variational analysis. Our book fits into this discipline, however, our main intention is to develop the analytical theory in close connection with the needs of applications in optimization and related subjects. Main Topics of the Book 1. Extended analysis of Lipschitz functions and their generalized derivatives, including "Newton maps" and regularity of multivalued mappings. 2. Principle of successive approximation under metric regularity and its - plication to implicit functions.

This book deals with the aspects of modeling and solving real-world optimiza- tion problems in a unique combination. It treats systematically the major mod- eling languages and modeling systems used to solve mathematical optimization problems. The book is an offspring ofthe 71 st Meeting of the GOR (Gesellschaft fill Operations Research) Working Group Mathematical Optimization in Real Life which was held under the title Modeling Languages in Mathematical Op- timization during April 23-25, 2003 in the German Physics Society Confer- ence Building in Bad Honnef, Germany. The modeling language providers AIMMS Johannes Bisschop, Paragon Decision Technology B. V, Haarlem, The Netherlands, AMPL Bob Fourer, Northwestern Univ.; David M. Gay, AMPL Optimization LLC. , NJ, GAMS Alexander Meeraus, GAMS Development Corporation, Washington D. C. , Mosel Bob Daniel, Dash Optimization, Blisworth, UK, MPL Bjami Krist jansson, Maximal Software, Arlington, VA, NOP-2 Hermann Schichl, Vienna University, Austria, PCOMP Klaus Schittkowski, Bayreuth University, Germany, and OPL Sofiane Oussedik, ILOG Inc. , Paris, France gave deep insight into their motivations and conceptual design features of their software, highlighted their advantages but also critically discussed their limits. The participants benefited greatly from this symposium which gave a useful overview and orientation on today's modeling languages in optimization. Roughly speaking, a modeling language serves the need to pass data and a mathematical model description to a solver in the same way that people, es- Of course, in pecially mathematicians describe those problems to each other.

A cooperative system is defined to be multiple dynamic entities that share information or tasks to accomplish a common, though perhaps not singular, objective. Examples of cooperative control systems might include: robots operating within a manufacturing cell, unmanned aircraft in search and rescue operations or military surveillance and attack missions, arrays of micro satellites that form a distributed large aperture radar, employees operating within an organization, and software agents. The term entity is most often associated with vehicles capable of physical motion such as robots, automobiles, ships, and aircraft, but the definition extends to any entity concept that exhibits a time dependent behavior. Critical to cooperation is communication, which may be accomplished through active message passing or by passive observation. It is assumed that cooperation is being used to accomplish some common purpose that is greater than the purpose of each individual, but we recognize that the individual may have other objectives as well, perhaps due to being a member of other caucuses. This implies that cooperation may assume hierarchical forms as well. The decision-making processes (control) are typically thought to be distributed or decentralized to some degree. For if not, a cooperative system could always be modeled as a single entity. The level of cooperation may be indicated by the amount of information exchanged between entities. Cooperative systems may involve task sharing and can consist of heterogeneous entities. Mixed initiative systems are particularly interesting heterogeneous systems since they are composed of humans and machines. Finally, one is often interested in how cooperative systems perform under noisy or adversary conditions. In December 2000, the Air Force Research Laboratory and the University of Florida successfully hosted the first Workshop on Cooperative Control and Optimization in Gainesville, Florida. This book contains selected refereed papers summarizing the participants' research in control and optimization of cooperative systems. Audience: Faculty, graduate students, and researchers in optimization and control, computer sciences and engineering.

Symmetry and Economic Invariance (second enhanced edition) explores how the symmetry and invariance of economic models can provide insights into their properties. Although the professional economist of today is adept at many of the mathematical techniques used in static and dynamic optimization models, group theory is still not among his or her repertoire of tools. The authors aim to show that group theoretic methods form a natural extension of the techniques commonly used in economics and that they can be easily mastered. Part I provides an introduction that minimizes prerequisites including prior knowledge of group theory. Part II discusses recent developments in the field.

This contributed volume considers recent advances in dynamic games and their applications, based on presentations given at the 17th Symposium of the International Society of Dynamic Games, held July 12-15, 2016, in Urbino, Italy. Written by experts in their respective disciplines, these papers cover various aspects of dynamic game theory including mean-field games, stochastic and pursuit-evasion games, and computational methods for dynamic games. Topics covered include Pedestrian flow in crowded environments Models for climate change negotiations Nash Equilibria for dynamic games involving Volterra integral equations Differential games in healthcare markets Linear-quadratic Gaussian dynamic games Aircraft control in wind shear conditions Advances in Dynamic and Mean-Field Games presents state-of-the-art research in a wide spectrum of areas. As such, it serves as a testament to the continued vitality and growth of the field of dynamic games and their applications. It will be of interest to an interdisciplinary audience of researchers, practitioners, and graduate students.

This volume covers recent developments in the design, operation, and management of mobile telecommunication and computer systems.

Uncertainty regarding loading and system parameters leads to challenging optimization and robustness issues. Stochastic modeling combined with optimization theory ensures the optimum end-to-end performance of telecommunication or computer network systems. In view of the diverse design options possible, supporting models have many adjustable parameters and choosing the best set for a particular performance objective is delicate and time-consuming. An optimization based approach determines the optimal possible allocation for these parameters.

Researchers and graduate students working at the interface of telecommunications and operations research will benefit from this book. Due to the practical approach, this book will also serve as a reference tool for scientists and engineers in telecommunication and computer networks who depend upon optimization.

In this book methods from Operations Research and Game Theory are used to determine companies' profit-maximizing strategies related to pricing and (cooperative) advertising. It considers different supply chain structures as well as various distributions of power, making it possible to analyze both inter-echelon and intra-echelon dependencies between the companies' decisions. Additionally, an approach based on fuzzy set theory is presented in order to compensate for incomplete or missing data on market characteristics. Vertical cooperative advertising is an essential element of partnerships between manufacturers and retailers, allowing manufacturers to financially support their retailers' advertising efforts so as to increase sales for the entire supply chain. Given that such programs not only make up a considerable part of many companies' advertising budgets, but are also a controversial subject in many business relations, their correct design is of particular importance.

The project of writing this monograph was conceived in August 2006. It is a m- ter of delight and satisfaction that this monograph would be published during the centenary year (May 27, 2008 - May 26, 2009) of our dear alma mater, the Indian Institute of Science, which is truly a magni cent temple and an eternal source of inspiration, with a splendid ambiance for research. Studying the rational behavior of entities interacting with each other in or- nized or ad-hoc marketplaces has been the bread and butter of our research group here at the Electronic Commerce Laboratory, Department of Computer Science and Automation, Indian Institute of Science. Speci cally, the application of game th- retic modeling and mechanism design principles to the area of network economics was an area of special interest to the authors. In fact, the dissertations of the s- ond, third, and fourth authors (Dinesh Garg, Ramasuri Narayanam, and Hastagiri Prakash) were all in this area. Dinesh Garg's Doctoral Thesis, which later won the Best Dissertation Award at the Department of Computer Science and Automation, Indian Institute of Science for the academic year 2006-07, included an interesting chapter on applying the brilliant work of Roger Myerson (Nobel laureate in E- nomic Sciences in 2007) to the topical problem of sponsored search auctions on the web. Ramasuri's Master's work applied mechanism design to develop robust broadcastprotocolsin wireless adhoc networkswhile Hastagiri's Master's work - veloped resource allocation mechanisms for computational grids.

Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linear programming can be extended to semidefinite programming.
In this monograph the basic theory of interior point algorithms is explained. This includes the latest results on the properties of the central path as well as the analysis of the most important classes of algorithms. Several "classic" applications of semidefinite programming are also described in detail. These include the Lov sz theta function and the MAX-CUT approximation algorithm by Goemans and Williamson.
Audience: Researchers or graduate students in optimization or related fields, who wish to learn more about the theory and applications of semidefinite programming.

In science, engineering and economics, decision problems are frequently modelled by optimizing the value of a (primary) objective function under stated feasibility constraints. In many cases of practical relevance, the optimization problem structure does not warrant the global optimality of local solutions; hence, it is natural to search for the globally best solution(s). Global Optimization in Action provides a comprehensive discussion of adaptive partition strategies to solve global optimization problems under very general structural requirements. A unified approach to numerous known algorithms makes possible straightforward generalizations and extensions, leading to efficient computer-based implementations. A considerable part of the book is devoted to applications, including some generic problems from numerical analysis, and several case studies in environmental systems analysis and management. The book is essentially self-contained and is based on the author's research, in cooperation (on applications) with a number of colleagues. Audience: Professors, students, researchers and other professionals in the fields of operations research, management science, industrial and applied mathematics, computer science, engineering, economics and the environmental sciences.

The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimisation. While its applications cut across an wide range of activities, many of the applications are only known to specialists. The aim of this handbook is to correct this. It has long been recognized that modelling is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years, it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It will be done in an academic handbook treatment outlining the state-of-the-art for researchers across the domains of the Computer Science, Math Programming, Applied Mathematics, Engineering, and Operations Research. Computer Science, and Combinatorics.

This book develops a new approach called parameter advising for finding a parameter setting for a sequence aligner that yields a quality alignment of a given set of input sequences. In this framework, a parameter advisor is a procedure that automatically chooses a parameter setting for the input, and has two main ingredients: (a) the set of parameter choices considered by the advisor, and (b) an estimator of alignment accuracy used to rank alignments produced by the aligner. On coupling a parameter advisor with an aligner, once the advisor is trained in a learning phase, the user simply inputs sequences to align, and receives an output alignment from the aligner, where the advisor has automatically selected the parameter setting. The chapters first lay out the foundations of parameter advising, and then cover applications and extensions of advising. The content * examines formulations of parameter advising and their computational complexity, * develops methods for learning good accuracy estimators, * presents approximation algorithms for finding good sets of parameter choices, and * assesses software implementations of advising that perform well on real biological data. Also explored are applications of parameter advising to * adaptive local realignment, where advising is performed on local regions of the sequences to automatically adapt to varying mutation rates, and * ensemble alignment, where advising is applied to an ensemble of aligners to effectively yield a new aligner of higher quality than the individual aligners in the ensemble. The book concludes by offering future directions in advising research.