Algorithms For Continuous Optimization

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Algorithms for Continuous Optimization

Author : E. Spedicato
Publisher : Springer Science & Business Media
ISBN 13 : 9400903693
Total Pages : 572 pages
Book Rating : 4.4/5 (9 download)

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Book Synopsis Algorithms for Continuous Optimization by : E. Spedicato

Download or read book Algorithms for Continuous Optimization written by E. Spedicato and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NATO Advanced Study Institute on "Algorithms for continuous optimiza tion: the state of the art" was held September 5-18, 1993, at II Ciocco, Barga, Italy. It was attended by 75 students (among them many well known specialists in optimiza tion) from the following countries: Belgium, Brasil, Canada, China, Czech Republic, France, Germany, Greece, Hungary, Italy, Poland, Portugal, Rumania, Spain, Turkey, UK, USA, Venezuela. The lectures were given by 17 well known specialists in the field, from Brasil, China, Germany, Italy, Portugal, Russia, Sweden, UK, USA. Solving continuous optimization problems is a fundamental task in computational mathematics for applications in areas of engineering, economics, chemistry, biology and so on. Most real problems are nonlinear and can be of quite large size. Devel oping efficient algorithms for continuous optimization has been an important field of research in the last 30 years, with much additional impetus provided in the last decade by the availability of very fast and parallel computers. Techniques, like the simplex method, that were already considered fully developed thirty years ago have been thoroughly revised and enormously improved. The aim of this ASI was to present the state of the art in this field. While not all important aspects could be covered in the fifty hours of lectures (for instance multiob jective optimization had to be skipped), we believe that most important topics were presented, many of them by scientists who greatly contributed to their development.

Algorithms for Convex Optimization

Author : Nisheeth K. Vishnoi
Publisher : Cambridge University Press
ISBN 13 : 1108633994
Total Pages : 314 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Algorithms for Convex Optimization by : Nisheeth K. Vishnoi

Download or read book Algorithms for Convex Optimization written by Nisheeth K. Vishnoi and published by Cambridge University Press. This book was released on 2021-10-07 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous optimization problems. For problems like maximum flow, maximum matching, and submodular function minimization, the fastest algorithms involve essential methods such as gradient descent, mirror descent, interior point methods, and ellipsoid methods. The goal of this self-contained book is to enable researchers and professionals in computer science, data science, and machine learning to gain an in-depth understanding of these algorithms. The text emphasizes how to derive key algorithms for convex optimization from first principles and how to establish precise running time bounds. This modern text explains the success of these algorithms in problems of discrete optimization, as well as how these methods have significantly pushed the state of the art of convex optimization itself.

An Introduction to Continuous Optimization

Author : Niclas Andreasson
Publisher : Courier Dover Publications
ISBN 13 : 0486802876
Total Pages : 515 pages
Book Rating : 4.4/5 (868 download)

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Book Synopsis An Introduction to Continuous Optimization by : Niclas Andreasson

Download or read book An Introduction to Continuous Optimization written by Niclas Andreasson and published by Courier Dover Publications. This book was released on 2020-01-15 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: This treatment focuses on the analysis and algebra underlying the workings of convexity and duality and necessary/sufficient local/global optimality conditions for unconstrained and constrained optimization problems. 2015 edition.

Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming

Author : Mohit Tawarmalani
Publisher : Springer Science & Business Media
ISBN 13 : 1475735324
Total Pages : 492 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming by : Mohit Tawarmalani

Download or read book Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming written by Mohit Tawarmalani and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in constrained optimization originated with the simple linear pro gramming model since it was practical and perhaps the only computationally tractable model at the time. Constrained linear optimization models were soon adopted in numerous application areas and are perhaps the most widely used mathematical models in operations research and management science at the time of this writing. Modelers have, however, found the assumption of linearity to be overly restrictive in expressing the real-world phenomena and problems in economics, finance, business, communication, engineering design, computational biology, and other areas that frequently demand the use of nonlinear expressions and discrete variables in optimization models. Both of these extensions of the linear programming model are NP-hard, thus representing very challenging problems. On the brighter side, recent advances in algorithmic and computing technology make it possible to re visit these problems with the hope of solving practically relevant problems in reasonable amounts of computational time. Initial attempts at solving nonlinear programs concentrated on the de velopment of local optimization methods guaranteeing globality under the assumption of convexity. On the other hand, the integer programming liter ature has concentrated on the development of methods that ensure global optima. The aim of this book is to marry the advancements in solving nonlinear and integer programming models and to develop new results in the more general framework of mixed-integer nonlinear programs (MINLPs) with the goal of devising practically efficient global optimization algorithms for MINLPs.

Global Optimization in Action

Author : János D. Pintér
Publisher : Springer Science & Business Media
ISBN 13 : 1475725027
Total Pages : 481 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Global Optimization in Action by : János D. Pintér

Download or read book Global Optimization in Action written by János D. Pintér and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

A Brief Introduction to Continuous Evolutionary Optimization

Author : Oliver Kramer
Publisher : Springer Science & Business Media
ISBN 13 : 3319034227
Total Pages : 94 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis A Brief Introduction to Continuous Evolutionary Optimization by : Oliver Kramer

Download or read book A Brief Introduction to Continuous Evolutionary Optimization written by Oliver Kramer and published by Springer Science & Business Media. This book was released on 2013-12-04 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima. A selection operator based on reference lines in objective space is introduced to optimize multiple conflictive objectives. Evolutionary search is employed for learning kernel parameters of the Nadaraya-Watson estimator and a swarm-based iterative approach is presented for optimizing latent points in dimensionality reduction problems. Experiments on typical benchmark problems as well as numerous figures and diagrams illustrate the behavior of the introduced concepts and methods.

An Introduction to Continuous Optimization

Author : Niclas Andréasson
Publisher :
ISBN 13 : 9789144115290
Total Pages : pages
Book Rating : 4.1/5 (152 download)

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Book Synopsis An Introduction to Continuous Optimization by : Niclas Andréasson

Download or read book An Introduction to Continuous Optimization written by Niclas Andréasson and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Algorithms for Optimization

Author : Mykel J. Kochenderfer
Publisher : MIT Press
ISBN 13 : 0262039427
Total Pages : 521 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Algorithms for Optimization by : Mykel J. Kochenderfer

Download or read book Algorithms for Optimization written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2019-03-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.

Continuous Optimization

Author : V. Jeyakumar
Publisher : Springer Science & Business Media
ISBN 13 : 0387267719
Total Pages : 454 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Continuous Optimization by : V. Jeyakumar

Download or read book Continuous Optimization written by V. Jeyakumar and published by Springer Science & Business Media. This book was released on 2006-03-09 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuous optimization is the study of problems in which we wish to opti mize (either maximize or minimize) a continuous function (usually of several variables) often subject to a collection of restrictions on these variables. It has its foundation in the development of calculus by Newton and Leibniz in the 17*^ century. Nowadys, continuous optimization problems are widespread in the mathematical modelling of real world systems for a very broad range of applications. Solution methods for large multivariable constrained continuous optimiza tion problems using computers began with the work of Dantzig in the late 1940s on the simplex method for linear programming problems. Recent re search in continuous optimization has produced a variety of theoretical devel opments, solution methods and new areas of applications. It is impossible to give a full account of the current trends and modern applications of contin uous optimization. It is our intention to present a number of topics in order to show the spectrum of current research activities and the development of numerical methods and applications.

Numerical Optimization

Author : Jorge Nocedal
Publisher : Springer Science & Business Media
ISBN 13 : 0387400656
Total Pages : 664 pages
Book Rating : 4.3/5 (874 download)

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Book Synopsis Numerical Optimization by : Jorge Nocedal

Download or read book Numerical Optimization written by Jorge Nocedal and published by Springer Science & Business Media. This book was released on 2006-12-11 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

Anintroduction to Continuous Optimization / Second Edition

Author : Niclas Andreasson
Publisher : Studentlitteratur AB
ISBN 13 : 9789144060774
Total Pages : 484 pages
Book Rating : 4.0/5 (67 download)

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Book Synopsis Anintroduction to Continuous Optimization / Second Edition by : Niclas Andreasson

Download or read book Anintroduction to Continuous Optimization / Second Edition written by Niclas Andreasson and published by Studentlitteratur AB. This book was released on 2013-10-01 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimisation, or mathematical programming, is a fundamental subject within decision science and operations research, in which mathematical decision models are constructed, analysed, and solved. The books focus lies on providing a basis for the analysis of optimisation models and of candidate optimal solutions for continuous optimisation models. The main part of the mathematical material therefore concerns the analysis and linear algebra that underlie the workings of convexity and duality, and necessary/sufficient local/global optimality conditions for continuous optimisation problems. Natural algorithms are then developed from these optimality conditions, and their most important convergence characteristics are analysed. The book answers many more questions of the form Why? and Why not? than How?. We use only elementary mathematics in the development of the book, yet are rigorous throughout. The book provides lecture, exercise and reading material for a first course on continuous optimisation and mathematical programming, geared towards third-year students, and has already been used as such for nearly ten years. The preface to the second edition describes the main changes made since the first, 2005, edition. The book can be used in mathematical optimisation courses at any mathematics, engineering, economics, and business schools. It is a perfect starting book for anyone who wishes to develop his/her understanding of the subject of optimisation, before actually applying it.

Algorithms for Continuous Optimization

Author : Emilio Goiuseppe Spedicato
Publisher : Springer Science & Business Media
ISBN 13 : 9780792328599
Total Pages : 596 pages
Book Rating : 4.3/5 (285 download)

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Book Synopsis Algorithms for Continuous Optimization by : Emilio Goiuseppe Spedicato

Download or read book Algorithms for Continuous Optimization written by Emilio Goiuseppe Spedicato and published by Springer Science & Business Media. This book was released on 1994-05-31 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NATO Advanced Study Institute on "Algorithms for continuous optimiza tion: the state of the art" was held September 5-18, 1993, at II Ciocco, Barga, Italy. It was attended by 75 students (among them many well known specialists in optimiza tion) from the following countries: Belgium, Brasil, Canada, China, Czech Republic, France, Germany, Greece, Hungary, Italy, Poland, Portugal, Rumania, Spain, Turkey, UK, USA, Venezuela. The lectures were given by 17 well known specialists in the field, from Brasil, China, Germany, Italy, Portugal, Russia, Sweden, UK, USA. Solving continuous optimization problems is a fundamental task in computational mathematics for applications in areas of engineering, economics, chemistry, biology and so on. Most real problems are nonlinear and can be of quite large size. Devel oping efficient algorithms for continuous optimization has been an important field of research in the last 30 years, with much additional impetus provided in the last decade by the availability of very fast and parallel computers. Techniques, like the simplex method, that were already considered fully developed thirty years ago have been thoroughly revised and enormously improved. The aim of this ASI was to present the state of the art in this field. While not all important aspects could be covered in the fifty hours of lectures (for instance multiob jective optimization had to be skipped), we believe that most important topics were presented, many of them by scientists who greatly contributed to their development.

Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems

Author : Ryszard Kowalczyk
Publisher : Springer Science & Business Media
ISBN 13 : 3642044409
Total Pages : 876 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems by : Ryszard Kowalczyk

Download or read book Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems written by Ryszard Kowalczyk and published by Springer Science & Business Media. This book was released on 2009-09-23 with total page 876 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational collective intelligence (CCI) is most often understood as a subfield of artificial intelligence (AI) dealing with soft computing methods that enable group decisions to be made or knowledge to be processed among autonomous units acting in distributed environments. The needs for CCI techniques and tools have grown signi- cantly recently as many information systems work in distributed environments and use distributed resources. Web-based systems, social networks and multi-agent systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. Therefore, CCI is of great importance for today’s and future distributed systems. Methodological, theoretical and practical aspects of computational collective int- ligence, such as group decision making, collective action coordination, and knowledge integration, are considered as the form of intelligence that emerges from the collabo- tion and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc. , can support human and other collective intelligence and create new forms of CCI in natural and/or artificial s- tems.

Bayesian Heuristic Approach to Discrete and Global Optimization

Author : Jonas Mockus
Publisher : Springer Science & Business Media
ISBN 13 : 1475726279
Total Pages : 394 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Bayesian Heuristic Approach to Discrete and Global Optimization by : Jonas Mockus

Download or read book Bayesian Heuristic Approach to Discrete and Global Optimization written by Jonas Mockus and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This book is the first to demonstrate that this framework is also well suited for the exploitation of heuristic methods in the solution of such problems, especially those of large scale for which exact optimization approaches can be prohibitively costly. The book covers all aspects ranging from the formal presentation of the Bayesian Approach, to its extension to the Bayesian Heuristic Strategy, and its utilization within the informal, interactive Dynamic Visualization strategy. The developed framework is applied in forecasting, in neural network optimization, and in a large number of discrete and continuous optimization problems. Specific application areas which are discussed include scheduling and visualization problems in chemical engineering, manufacturing process control, and epidemiology. Computational results and comparisons with a broad range of test examples are presented. The software required for implementation of the Bayesian Heuristic Approach is included. Although some knowledge of mathematical statistics is necessary in order to fathom the theoretical aspects of the development, no specialized mathematical knowledge is required to understand the application of the approach or to utilize the software which is provided. Audience: The book is of interest to both researchers in operations research, systems engineering, and optimization methods, as well as applications specialists concerned with the solution of large scale discrete and/or nonconvex optimization problems in a broad range of engineering and technological fields. It may be used as supplementary material for graduate level courses.

Optimization techniques I

Author : Max Cerf
Publisher : EDP Sciences
ISBN 13 : 2759831647
Total Pages : 484 pages
Book Rating : 4.7/5 (598 download)

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Book Synopsis Optimization techniques I by : Max Cerf

Download or read book Optimization techniques I written by Max Cerf and published by EDP Sciences. This book was released on 2023-10-12T00:00:00+02:00 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book in two volumes provides an overview of continuous, discrete and functional optimization techniques. This first volume is devoted to continuous optimization, which deals with problems with real variables, without or with constraints. After a reminder of the optimality conditions and their geometrical interpretation, the topics covered are: -gradient-free algorithms that can be applied to any type of function; -unconstrained algorithms based on Newton-type descent methods; -algorithms with constraints: penalization, primal, dual and primal-dual methods; -linear programming with the simplex method and interior point methods. The emphasis is on understanding the principles rather than on mathematical rigor. Each concept or algorithm is accompanied by a detailed example to help you grasp the main ideas. This book is the result of 30 years of experience and is intended for students, researchers and engineers wishing to acquire a general knowledge in the field of optimization.

Linear Network Optimization

Author : Dimitri P. Bertsekas
Publisher : MIT Press
ISBN 13 : 9780262023344
Total Pages : 384 pages
Book Rating : 4.0/5 (233 download)

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Book Synopsis Linear Network Optimization by : Dimitri P. Bertsekas

Download or read book Linear Network Optimization written by Dimitri P. Bertsekas and published by MIT Press. This book was released on 1991 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems.

Global Optimization

Author : Marco Locatelli
Publisher : SIAM
ISBN 13 : 1611972671
Total Pages : 437 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Global Optimization by : Marco Locatelli

Download or read book Global Optimization written by Marco Locatelli and published by SIAM. This book was released on 2013-10-16 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a thorough overview of the rapidly growing field of global optimization, with chapters on key topics such as complexity, heuristic methods, derivation of lower bounds for minimization problems, and branch-and-bound methods and convergence. The final chapter offers both benchmark test problems and applications of global optimization, such as finding the conformation of a molecule or planning an optimal trajectory for interplanetary space travel. An appendix provides fundamental information on convex and concave functions. Intended for Ph.D. students, researchers, and practitioners looking for advanced solution methods to difficult optimization problems. It can be used as a supplementary text in an advanced graduate-level seminar.