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Planning (firm) --- Operational research. Game theory --- Nonlinear programming --- 519.85 --- 681.3*G16 --- Programming (Mathematics) --- Mathematical programming --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Nonlinear programming. --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.85 Mathematical programming --- Programmation mathematique --- Programmation non lineaire
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Planning (firm) --- Programming (Mathematics) --- 519.85 --- 681.3*G16 --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Mathematical optimization --- Operations research --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Programming (Mathematics). --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.85 Mathematical programming --- Programmation (mathématiques)
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Nonlinear programming --- 519.85 --- 681.3*G16 --- Mathematical programming --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.85 Mathematical programming
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Microfluidics for Biological Applications provides researchers and scientists in the biotechnology, pharmaceutical, and life science industries with an introduction to the basics of microfluidics and discusses how to link these technologies to various biological applications at the industrial and academic level. Readers will gain insight into a wide variety of biological applications for microfluidics. The book begins with a perspective on the history and development of microfluidic technologies, followed by an overview on how microfluidic systems have been used to study and manipulate specific classes of components, including a discussion of specific biological applications of microfluidics and concludes with a discussion of emerging trends in the field. Microfluidics for Biological Applications provides information about the latest techniques and trends including: Fabrication methods for microfluidic devices, including those using biodegradable materials Use of microfluidics for high throughput screening Microfluidic methods for detection of pathogens in diagnostic and biodefense applications Analysis and manipulation of DNA, proteins, and cells in a microfluidic device Use of microfluidic platforms for tissue engineering and vascularization Microfluidics for Biological Applications is an ideal reference for researchers and practicing engineers, as well as graduate students who are either entering the field for the first time, or those already conducting research and who want to expand their knowledge in the area of microfluidics.
#KVIV --- 519.85 --- 681.3*G16 --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.85 Mathematical programming --- Mathematical programming --- Programmation (mathématiques)
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A number of different problems of interest to the operational researcher and the mathematical economist - for example, certain problems of optimization on graphs and networks, of machine-scheduling, of convex analysis and of approx imation theory - can be formulated in a convenient way using the algebraic structure (R,$,@) where we may think of R as the (extended) real-number system with the binary combining operations x$y, x®y defined to be max(x,y),(x+y) respectively. The use of this algebraic structure gives these problems the character of problems of linear algebra, or linear operator theory. This fact hB.s been independently discovered by a number of people working in various fields and in different notations, and the starting-point for the present Lecture Notes was the writer's persuasion that the time had arrived to present a unified account of the algebra of linear transformations of spaces of n-tuples over (R,$,®),to demonstrate its relevance to operational research and to give solutions to the standard linear-algebraic problems which arise - e.g. the solution of linear equations exactly or approximately, the eigenvector eigenvalue problem andso on.Some of this material contains results of hitherto unpublished research carried out by the writer during the years 1970-1977.
Operational research. Game theory --- Algebras, Linear --- Matrices --- Maxima and minima --- 519.8 --- 512 --- 512.64 --- 681.3*G16 --- Operational research --- Algebra --- Linear and multilinear algebra. Matrix theory --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Business & Economics --- Economic Theory --- Algebras, Linear. --- Matrices. --- Maxima and minima. --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 512.64 Linear and multilinear algebra. Matrix theory --- 512 Algebra --- 519.8 Operational research
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Operational research. Game theory --- Operations research --- 519.85 --- 681.3*G16 --- 681.3*I28 --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Mathematical programming --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Problem solving, control methods and search: backtracking; dynamic program- ming; graph and tree search strategies; heuristics; plan execution, formationand generation (Artificial intelligence)--See also {681.3*F22} --- 681.3*I28 Problem solving, control methods and search: backtracking; dynamic program- ming; graph and tree search strategies; heuristics; plan execution, formationand generation (Artificial intelligence)--See also {681.3*F22} --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.85 Mathematical programming --- Programmation (mathématiques) --- Recherche opérationnelle
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Discrete Optimization I
Discrete programmering. --- Optimaliseren. --- Mathematical optimization. --- Optimisation mathématique --- Mathematical optimization --- 519.85 --- 681.3*F22 --- 681.3*G16 --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Mathematical programming --- Nonnumerical algorithms and problems: complexity of proof procedures; computations on discrete structures; geometrical problems and computations; pattern matching --See also {?681.3*E2-5}; {681.3*G2}; {?681.3*H2-3} --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 681.3*F22 Nonnumerical algorithms and problems: complexity of proof procedures; computations on discrete structures; geometrical problems and computations; pattern matching --See also {?681.3*E2-5}; {681.3*G2}; {?681.3*H2-3} --- 519.85 Mathematical programming --- Operational research. Game theory --- Mathematical analysis. --- 517.1 Mathematical analysis --- Programmation mathematique --- Colloque
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Theory of extremal problems
Mathematical optimization --- Maxima and minima --- Calculus of variations --- Extremal problems (Mathematics) --- Optimisation mathématique --- Maxima et minima --- Calcul des variations --- Problèmes extrémaux (Mathématiques) --- 519.85 --- 681.3*F22 --- 681.3*G16 --- Minima --- Mathematics --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Operations research --- Simulation methods --- System analysis --- Graph theory --- Problems, Extremal (Mathematics) --- Geometric function theory --- Isoperimetrical problems --- Variations, Calculus of --- Mathematical programming --- Nonnumerical algorithms and problems: complexity of proof procedures; computations on discrete structures; geometrical problems and computations; pattern matching --See also {?681.3*E2-5}; {681.3*G2}; {?681.3*H2-3} --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Extremal problems --- Calculus of variations. --- Mathematical optimization. --- Maxima and minima. --- Extremal problems (Mathematics). --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 681.3*F22 Nonnumerical algorithms and problems: complexity of proof procedures; computations on discrete structures; geometrical problems and computations; pattern matching --See also {?681.3*E2-5}; {681.3*G2}; {?681.3*H2-3} --- 519.85 Mathematical programming --- Optimisation mathématique --- Problèmes extrémaux (Mathématiques) --- ELSEVIER-B EPUB-LIV-FT
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