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Books > Science & Mathematics > Mathematics > Optimization
* What is the essence of the similarity between linearly
independent sets of columns of a matrix and forests in a graph?
* Why does the greedy algorithm produce a spanning tree of minimum
weight in a connected graph?
* Can we test in polynomial time whether a matrix is totally
unimodular?
Matroid theory examines and answers questions like these.
Seventy-five years of study of matroids has seen the development of
a rich theory with links to graphs, lattices, codes, transversals,
and projective geometries. Matroids are of fundamental importance
in combinatorial optimization and their applications extend into
electrical and structural engineering.
This book falls into two parts: the first provides a comprehensive
introduction to the basics of matroid theory, while the second
treats more advanced topics. The book contains over seven hundred
exercises and includes, for the first time in one place, proofs of
all of the major theorems in the subject. The last two chapters
review current research and list more than eighty unsolved problems
along with a description of the progress towards their solutions.
Reviews from previous edition:
"It includes more background, such as finite fields and finite
projective and affine geometries, and the level of the exercises is
well suited to graduate students. The book is well written and
includes a couple of nice touches ... this is a very useful book. I
recommend it highly both as an introduction to matroid theory and
as a reference work for those already seriously interested in the
subject, whether for its own sake or for its applications to other
fields." -- AMS Bulletin
"Whoever wants to know what is happening in one of the most
exciting chapters of combinatorics has no choice but to buy and
peruse Oxley's treatise." -- The Bulletin of Mathematics
"This book is an excellent graduate textbook and reference book on
matroid theory. The care that went into the writing of this book is
evident by the quality of the exposition." -- Mathematical Reviews
Transnational Cooperation: An Issue-Based Approach presents an
analysis of transnational cooperation or collective action that
stresses basic concepts and intuition. Throughout the book, authors
Clint Peinhardt and Todd Sandler identify factors that facilitate
and/or inhibit such cooperation. The first four chapters lay the
analytical foundations for the book, while the next nine chapters
apply the analysis to a host of exigencies and topics of great
import. The authors use elementary game theory as a tool for
illustrating the ideas put forth in the text. Game theory reminds
us that rational actors (for example, countries, firms, or
individuals) must account for the responses by other rational
actors. The book assumes no prior knowledge of game theory; all
game-theoretic concepts and analyses are explained in detail to the
reader. Peinhardt and Sandler also employ paired comparisons in
illustrating the book's concepts. The book is rich in applications
and covers a wide range of topics, including superbugs, civil wars,
money laundering, financial crises, drug trafficking, terrorism,
global health concerns, international trade liberalization, acid
rain, leadership, sovereignty, and many others. Students,
researchers, and policymakers alike have much to gain from
Transnational Cooperation. It is a crossover book for economics,
political science, and public policy.
The Oxford Handbook of the Economics of Networks represents the
frontier of research into how and why networks form, how they
influence behavior, how they help govern outcomes in an interactive
world, and how they shape collective decision making, opinion
formation, and diffusion dynamics. From a methodological
perspective, the contributors to this volume devote attention to
theory, field experiments, laboratory experiments, and
econometrics. Theoretical work in network formation, games played
on networks, repeated games, and the interaction between linking
and behavior is synthesized. A number of chapters are devoted to
studying social process mediated by networks. Topics here include
opinion formation, diffusion of information and disease, and
learning. There are also chapters devoted to financial contagion
and systemic risk, motivated in part by the recent financial
crises. Another section discusses communities, with applications
including social trust, favor exchange, and social collateral; the
importance of communities for migration patterns; and the role that
networks and communities play in the labor market. A prominent role
of networks, from an economic perspective, is that they mediate
trade. Several chapters cover bilateral trade in networks,
strategic intermediation, and the role of networks in international
trade. Contributions discuss as well the role of networks for
organizations. On the one hand, one chapter discusses the role of
networks for the performance of organizations, while two other
chapters discuss managing networks of consumers and pricing in the
presence of network-based spillovers. Finally, the authors discuss
the internet as a network with attention to the issue of net
neutrality.
Economic theory and philosophy have discussed concepts of fairness,
but the criteria of fairness are in each case absolute: a situation
is either fair or it is not. This book draws on these literatures
to propose two criteria of relative fairness, and a hierarchical
rule for the priority of application of these criteria, with a view
to comparison of practicable alternatives in public policy. A
veil-of-ignorance device of representation of rational fairness is
used to argue that these criteria are normatively relevant.
Applications to intergenerational fairness, fairness among regions
in the context of migration, externalities and Pigovian taxes, to
fair prices and wages, and to relative fairness in the status of
racial and caste groups are sketched. The book is designed with
real world public policy practice. Scholars with an interest in the
economic evaluation of public policy will find this compelling book
essential reading.
Visual novels (VNs), a ludic video game genre that pairs textual
fiction stories with anime-like images and varying degrees of
interactivity, have increased in popularity among Western audiences
in recent years. Despite originating in Japan, these stories have
made their way into global culture as a genre accessible for both
play and creation with wide-ranging themes from horror and
loneliness to sexuality. The History and Allure of Interactive
Visual Novels begins with a comprehensive overview of the visual
novel genre and the cultural evolution that led to its rise, then
explains the tropes and appeal of subgenres like bishojo (cute girl
games), detective games, horror, and eroge (erotic games). Finally,
the book explores the future of the genre in both user-generated
games and games from other genres that liberally borrow both
narrative and ludological themes from visual novels. Whether
you’re a long-standing fan of the genre or a newcomer looking for
a fresh experience, The History and Allure of Interactive Visual
Novels will provide an accessible and critically engaging overview
of a genre that is rich in storytelling yet often overlooked.
Game theory means rigorous strategic thinking. It s the art of
anticipating your opponent s next moves, knowing full well that
your rival is trying to do the same thing to you. Though parts of
game theory involve simple common sense, much is counterintuitive,
and it can only be mastered by developing a new way of seeing the
world. Using a diverse array of rich case studies from pop culture,
TV, movies, sports, politics, and history the authors show how
nearly every business and personal interaction has a game-theory
component to it. Mastering game theory will make you more
successful in business and life, and this lively book is the key to
that mastery."
Optimization is a key concept in mathematics, computer science, and
operations research, and is essential to the modeling of any
system, playing an integral role in computer-aided design.
Fundamentals of Optimization Techniques with Algorithms presents a
complete package of various traditional and advanced optimization
techniques along with a variety of example problems, algorithms and
MATLAB (c) code optimization techniques, for linear and nonlinear
single variable and multivariable models, as well as
multi-objective and advanced optimization techniques. It presents
both theoretical and numerical perspectives in a clear and
approachable way. In order to help the reader apply optimization
techniques in practice, the book details program codes and
computer-aided designs in relation to real-world problems. Ten
chapters cover, an introduction to optimization; linear
programming; single variable nonlinear optimization; multivariable
unconstrained nonlinear optimization; multivariable constrained
nonlinear optimization; geometric programming; dynamic programming;
integer programming; multi-objective optimization; and
nature-inspired optimization. This book provides accessible
coverage of optimization techniques, and helps the reader to apply
them in practice.
This book addresses the mathematical and the practical aspects of
motion implied by advanced control theory. The richness and power
of the theory are demonstrated by separate analyses of single-model
and multi-modal repertoires, consisting of verities of estimation
and control facets. Starting with purely mathematical concepts,
specifically, abstract probability and information theories, model
control theory is gradually revealed as a rather amazing domain.
The mathematical equations, taking essentially simple forms, are
exposed as powerful generators of motion. Moreover, seemingly
obvious applications of the theory, such as high-performance
aircraft control make room for unexpected virtual reality feedback
in control of motion for the neurologically impaired.Following the
presentation of some historical milestones and mathematical
preliminaries, the book is divided into four parts. The first deals
with minimal-order models of state estimation and control. The
second addresses multi-modal estimation and control, which
facilitates the operation of high-performance aircraft in large
flight envelopes. The third presents the transition from naturally
nonlinear control of movement in obstacle avoidance and object
targeting to virtually linear control of movement in the
neurologically impaired. The fourth and final part of the book
addresses the application of virtual sensory feedback in walking
with specific neurological impairment. While the clinical studies
reported were all based on a single-model paradigm, a later
reflection reveals that, given the variety of neurological symptoms
associated with the relevant disorders, a multi-modal approach, as
that addressed in the control of high-performance aircraft in a
large flight envelope, would be similarly applicable in the
treatment of neurological disorders.
The book addresses optimization in the petroleum industry from a
practical, large-scale-application-oriented point of view. The
models and techniques presented help to optimize the limited
resources in the industry in order to maximize economic benefits,
ensure operational safety, and reduce environmental impact. The
book discusses several important real-life applications of
optimization in the petroleum industry, ranging from the scheduling
of personnel time to the blending of gasoline. It covers a wide
spectrum of relevant activities, including drilling, producing,
maintenance, and distribution. The text begins with an introductory
overview of the petroleum industry and then of optimization models
and techniques. The main body of the book details a variety of
applications of optimization models and techniques within the
petroleum industry. Applied Optimization in the Petroleum
Industry helps readers to find effective optimization-based
solutions to their own practical problems in a large and important
industrial sector, still the main source of the world’s energy
and the source of raw materials for a wide variety of industrial
and consumer products.
Many applications, including computer vision, computer arithmetic,
deep learning, entanglement in quantum information, graph theory
and energy networks, can be successfully tackled within the
framework of polynomial optimization, an emerging field with
growing research efforts in the last two decades. One key advantage
of these techniques is their ability to model a wide range of
problems using optimization formulations. Polynomial optimization
heavily relies on the moment-sums of squares (moment-SOS) approach
proposed by Lasserre, which provides certificates for positive
polynomials. On the practical side, however, there is 'no free
lunch' and such optimization methods usually encompass severe
scalability issues. Fortunately, for many applications, including
the ones formerly mentioned, we can look at the problem in the eyes
and exploit the inherent data structure arising from the cost and
constraints describing the problem.This book presents several
research efforts to resolve this scientific challenge with
important computational implications. It provides the development
of alternative optimization schemes that scale well in terms of
computational complexity, at least in some identified class of
problems. It also features a unified modeling framework to handle a
wide range of applications involving both commutative and
noncommutative variables, and to solve concretely large-scale
instances. Readers will find a practical section dedicated to the
use of available open-source software libraries.This
interdisciplinary monograph is essential reading for students,
researchers and professionals interested in solving optimization
problems with polynomial input data.
This book covers an introduction to convex optimization, one of the
powerful and tractable optimization problems that can be
efficiently solved on a computer. The goal of the book is tohelp
develop a sense of what convex optimization is, and how it can be
used in a widening array of practical contexts with a particular
emphasis on machine learning.The first part of the book covers core
concepts of convex sets, convex functions, and related basic
definitions that serve understanding convex optimization and its
corresponding models. The second part deals with one very useful
theory, called duality, which enables us to: (1) gain algorithmic
insights; and (2) obtain an approximate solution to non-convex
optimization problems which are often difficult to solve. The last
part focuses on modern applications in machine learning and deep
learning.A defining feature of this book is that it succinctly
relates the "story" of how convex optimization plays a role, via
historical examples and trending machine learning applications.
Another key feature is that it includes programming implementation
of a variety of machine learning algorithms inspired by
optimization fundamentals, together with a brief tutorial of the
used programming tools. The implementation is based on Python,
CVXPY, and TensorFlow. This book does not follow a traditional
textbook-style organization, but is streamlined via a series of
lecture notes that are intimately related, centered around coherent
themes and concepts. It serves as a textbook mainly for a
senior-level undergraduate course, yet is also suitable for a
first-year graduate course. Readers benefit from having a good
background in linear algebra, some exposure to probability, and
basic familiarity with Python.
Developments in the use of game theory have impacted multiple
fields and created opportunities for new applications. With the
ubiquity of these developments, there is an increase in the overall
utilization of this approach. Game Theory: Breakthroughs in
Research and Practice contains a compendium of the latest academic
material on the usage, strategies, and applications for
implementing game theory across a variety of industries and fields.
Including innovative studies on economics, military strategy, and
political science, this multi-volume book is an ideal source for
professionals, practitioners, graduate students, academics, and
researchers interested in the applications of game theory.
Extremum Seeking through Delays and PDEs, the first book on the
topic, expands the scope of applicability of the extremum seeking
method, from static and finite-dimensional systems to
infinite-dimensional systems. Readers will find: Numerous
algorithms for model-free real-time optimization are developed and
their convergence guaranteed. Extensions from single-player
optimization to noncooperative games, under delays and pdes, are
provided. The delays and pdes are compensated in the control
designs using the pde backstepping approach, and stability is
ensured using infinite-dimensional versions of averaging theory.
Accessible and powerful tools for analysis. This book is intended
for control engineers in all disciplines (electrical, mechanical,
aerospace, chemical), mathematicians, physicists, biologists, and
economists. It is appropriate for graduate students, researchers,
and industrial users.
This book is a scientific basis for understanding the urgent need
for a Great Transformation to a third step in social evolution.
Already being a community of common destiny, humanity can form an
actual unity through diversity to avoid extinction. Social actors
can recognise informational imperatives for cognition,
communication and co-operation to achieve such a unity. By doing
so, they apply a logic that underlies the structuration of any
agency, which is a real logic of self-organising systems from the
physical to the social. This logic is the Logic of the Third - the
Third is a meta-structure that emerges in a leap. The agents
interact and when they co-act they are likely to form a real
meta-structure of organisational relations. Informational agents
anticipate this by generating requisite information in their
attempt to cope with complex challenges. Such an information is a
meta-structure too. The Third helps achieve synergy effects.This
book discusses considerations from philosophy, systems theory, the
study of information, social systems, social information, ecology
and technology. It addresses ethical issues connected with the
long-forgotten arms race in an atomic age, the global warming not
yet under control, the pandemic misunderstood, the social question
still unanswered.
Nature-Inspired Optimization Algorithms provides a systematic
introduction to all major nature-inspired algorithms for
optimization. The book's unified approach, balancing algorithm
introduction, theoretical background and practical implementation,
complements extensive literature with well-chosen case studies to
illustrate how these algorithms work. Topics include particle swarm
optimization, ant and bee algorithms, simulated annealing, cuckoo
search, firefly algorithm, bat algorithm, flower algorithm, harmony
search, algorithm analysis, constraint handling, hybrid methods,
parameter tuning and control, as well as multi-objective
optimization. This book can serve as an introductory book for
graduates, doctoral students and lecturers in computer science,
engineering and natural sciences. It can also serve a source of
inspiration for new applications. Researchers and engineers as well
as experienced experts will also find it a handy reference.
This book presents a short introduction to continuous-time
financial models. An overview of the basics of stochastic analysis
precedes a focus on the Black-Scholes and interest rate models.
Other topics covered include self-financing strategies, option
pricing, exotic options and risk-neutral probabilities. Vasicek,
Cox-Ingersoll-Ross, and Heath-Jarrow-Morton interest rate models
are also explored. The author presents practitioners with a basic
introduction, with more rigorous information provided for
mathematicians. The reader is assumed to be familiar with the
basics of probability theory. Some basic knowledge of stochastic
integration and differential equations theory is preferable,
although all preliminary information is given in the first part of
the book. Some relatively simple theoretical exercises are also
provided.
Topology Optimization in Engineering Structure Design explores the
recent advances and applications of topology optimization in
engineering structures design, with a particular focus on aircraft
and aerospace structural systems. To meet the increasingly complex
engineering challenges provided by rapid developments in these
industries, structural optimization techniques have developed in
conjunction with them over the past two decades. The latest methods
and theories to improve mechanical performances and save structural
weight under static, dynamic and thermal loads are summarized and
explained in detail here, in addition to potential applications of
topology optimization techniques such as shape preserving design,
smart structure design and additive manufacturing. These new design
strategies are illustrated by a host of worked examples, which are
inspired by real engineering situations, some of which have been
applied to practical structure design with significant effects.
Written from a forward-looking applied engineering perspective, the
authors not only summarize the latest developments in this field of
structure design but also provide both theoretical knowledge and a
practical guideline. This book should appeal to graduate students,
researchers and engineers, in detailing how to use topology
optimization methods to improve product design.
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