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Foundations of genetic algorithms 6
Authors: --- ---
ISBN: 1281072893 9786611072896 0080506879 9780080506876 155860734X 9781558607347 Year: 2001 Publisher: San Francisco : Morgan Kaufmann,

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Foundations of Genetic Algorithms, Volume 6 is the latest in a series of books that records the prestigious Foundations of Genetic Algorithms Workshops, sponsored and organised by the International Society of Genetic Algorithms specifically to address theoretical publications on genetic algorithms and classifier systems.Genetic algorithms are one of the more successful machine learning methods. Based on the metaphor of natural evolution, a genetic algorithm searches the available information in any given task and seeks the optimum solution by replacing weaker populations with stronger


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Particle swarm optimization : theory, techniques and applications
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ISBN: 9781613247006 1613247001 9781616685270 1616685271 Year: 2011 Publisher: Hauppauge, N.Y. : Nova Science Publishers,

Principles of Network Economics
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ISBN: 1280346868 9786610346868 354029936X 3540276939 Year: 2006 Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer,

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Network problems are manifold and extremely complex. Many problems result from engineering details or mathematical difficulties, others are caused by disregarding economic principles and imperfections of markets. The text provides a fairly integrated approach of transportation related "network problems" and their "solutions" with emphasis on economics or, more precisely, microeconomic theory.


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Optimization and stability theory for economic analysis
Authors: ---
ISBN: 0521336058 0521333075 0511559402 9780521336055 9780521333078 9780511559402 Year: 1990 Publisher: Cambridge Cambridge University Press

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This book presents a coherent and systematic exposition of the mathematical theory of the problems of optimization and stability. Both of these are topics central to economic analysis since the latter is so much concerned with the optimizing behaviour of economic agents and the stability of the interaction processes to which this gives rise. The topics covered include convexity, mathematical programming, fixed point theorems, comparative static analysis and duality, the stability of dynamic systems, the calculus of variations and optimal control theory. The authors present a more detailed and wide-ranging discussion of these topics than is to be found in the few books which attempt a similar coverage. Although the text deals with fairly advanced material, the mathematical prerequisites are minimised by the inclusion of an integrated mathematical review designed to make the text self-contained and accessible to the reader with only an elementary knowledge of calculus and linear algebra. A novel feature of the book is that it provides the reader with an understanding and feel for the kinds of mathematical techniques most useful for dealing with particular economic problems. This is achieved through an extensive use of a broad range of economic examples (rather than the numerical/algebraic examples so often found).This is suitable for use in advanced undergraduate and postgraduate courses in economic analysis and should in addition prove a useful reference work for practising economists.

Foundations of dynamic economic analysis : optimal control theory and applications
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ISBN: 0521842727 0521603684 1107713773 0511081413 0511806825 1280163267 0511197128 0511121873 9780521603683 9780521842723 Year: 2005 Publisher: Cambridge : Cambridge University Press,

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Foundations of Dynamic Economic Analysis presents a modern and thorough exposition of the fundamental mathematical formalism used to study optimal control theory, i.e., continuous time dynamic economic processes, and to interpret dynamic economic behavior. The style of presentation, with its continual emphasis on the economic interpretation of mathematics and models, distinguishes it from several other excellent texts on the subject. This approach is aided dramatically by introducing the dynamic envelope theorem and the method of comparative dynamics early in the exposition. Accordingly, motivated and economically revealing proofs of the transversality conditions come about by use of the dynamic envelope theorem. Furthermore, such sequencing of the material naturally leads to the development of the primal-dual method of comparative dynamics and dynamic duality theory, two modern approaches used to tease out the empirical content of optimal control models. The stylistic approach ultimately draws attention to the empirical richness of optimal control theory, a feature missing in virtually all other textbooks of this type.


Book
Optimal Control of ODEs and DAEs
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ISBN: 3110249995 3110249952 9783110249996 9783110249958 Year: 2011 Publisher: Berlin ; Boston : De Gruyter,

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The intention of this textbook is to provide both, the theoretical and computational tools that are necessary to investigate and to solve optimal control problems with ordinary differential equations and differential-algebraic equations. An emphasis is placed on the interplay between the continuous optimal control problem, which typically is defined and analyzed in a Banach space setting, and discrete optimal control problems, which are obtained by discretization and lead to finite dimensional optimization problems. The book addresses primarily master and PhD students as well as researchers in applied mathematics, but also engineers or scientists with a good background in mathematics and interest in optimal control. The theoretical parts of the book require some knowledge of functional analysis, the numerically oriented parts require knowledge from linear algebra and numerical analysis. Examples are provided for illustration purposes.

Advanced stochastic models, risk assessment, and portfolio optimization : the ideal risk, uncertainty, and performance measures
Authors: --- ---
ISBN: 1281217301 0470253606 9786611217303 1283272954 9786613272959 1118086147 047005316X 9780470253601 9781281217301 9781118086148 9780470053164 6611217304 9781283272957 6613272957 Year: 2008 Publisher: Hoboken, N.J. : [Chichester : Wiley ; John Wiley, distributor],

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This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers.


Book
Resource allocation problems in supply chains
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ISBN: 9781785603983 1785603981 178560399X 9781785603990 9781785603990 Year: 2015 Publisher: Bingley : Emerald Insight,

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Resource Allocation is the utilization of available resources in the system. This book focuses on development of models for 6 new, complex classes of RA problems in Supply Chain networks, focusing on bi-objectives, dynamic input data, and multiple performance measure based allocation and integrated allocation, and routing with complex constraints.


Book
Optimization for machine learning
Authors: --- ---
ISBN: 9780262298773 0262298775 1283302845 9781283302845 9780262016469 026201646X 0262297892 9786613302847 Year: 2012 Publisher: Cambridge: MIT Press,

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An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities.The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields.Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

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