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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
Genetic algorithms --- Mathematical optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- E-books
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Swarm intelligence --- Mathematical optimization --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Collective intelligence --- Cellular automata --- Distributed artificial intelligence --- E-books --- Swarm intelligence. --- Mathematical optimization.
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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.
Transportation --- Network analysis (Planning) --- Planning --- Mathematical models. --- Project networks --- Microeconomics. --- Mathematical optimization. --- Optimization. --- Price theory --- Economics --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- AA / International- internationaal --- 303.8 --- 385.0 --- Econometrische behandeling van een onderwerp. --- Vervoerwezen, verkeerswegen en -middelen: algemeenheden. --- Econometrische behandeling van een onderwerp --- Vervoerwezen, verkeerswegen en -middelen: algemeenheden
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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.
Quantitative methods (economics) --- Mathematical optimization. --- Economics, Mathematical. --- AA / International- internationaal --- 330.2 --- Economische analyse en research. Theorie van de informatie. --- Mathematical optimization --- Economics, Mathematical --- Economische analyse en research. Theorie van de informatie --- Business, Economy and Management --- Economics --- Mathematical economics --- Econometrics --- Mathematics --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Methodology
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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.
Mathematical control systems --- Economics --- Control theory --- Mathematical optimization --- Mathematical models --- Control theory. --- Mathematical optimization. --- Mathematical models. --- AA / International- internationaal --- 305.971 --- Speciale gevallen in econometrische modelbouw. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Economics, Mathematical --- Dynamics --- Machine theory --- Speciale gevallen in econometrische modelbouw --- Business, Economy and Management --- Economics - Mathematical models
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Engineering design --- -Mathematical optimization --- -Structural design --- -Engineering design --- Architectural design --- Strains and stresses --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Design, Engineering --- Engineering --- Industrial design --- Mathematical models --- -Congresses --- Congresses --- Data processing --- Design --- -Mathematical models --- Mathematical optimization --- Structural design --- Mathematical models&delete& --- Data processing&delete& --- Optimalisation (contraintes)
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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.
Control theory - Mathematical models. --- Control theory -- Mathematical models. --- Mathematical optimization. --- Mathematics. --- Optimal control. --- Control theory --- Mathematical optimization --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Operations Research --- Mathematical models --- Mathematical models. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- E-books --- Control Theory. --- DAE. --- ODE. --- Optimal.
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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.
Stochastic processes. --- Mathematical optimization. --- Risk assessment --- Portfolio management --- Mathematical models. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Random processes --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Probabilities --- Stochastic processes --- Mathematical optimization --- Mathematical models --- E-books --- Investment management
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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.
E-books --- Business logistics --- Resource allocation --- Mathematical optimization. --- Programming (Mathematics) --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Mathematical optimization --- Operations research --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Simulation methods --- System analysis --- Mathematical models. --- Allocation of resources --- Resources allocation --- Economics --- Management --- Organization --- Planning --- Feasibility studies --- Supply chain management --- Industrial management --- Logistics
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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.
Machine learning --- Mathematical optimization --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Learning, Machine --- Artificial intelligence --- Machine theory --- Mathematical models --- E-books --- Mathematical optimization. --- Mathematical models. --- COMPUTER SCIENCE/Machine Learning & Neural Networks --- COMPUTER SCIENCE/Artificial Intelligence --- Machine learning - Mathematical models
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