Optimization in a Complex World

Optimization in a Complex World PDF Author: Victor Korotkikh
Publisher:
ISBN: 9780387886657
Category : Mathematical optimization
Languages : en
Pages : 325

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Book Description
As complex systems play an increasingly important role in human activities, optimisation becomes a critical issue. This book suggests a new perspective to the problem by recognising the possibility of a general optimality condition that determines the optimal performance of a complex system.

Optimization in a Complex World

Optimization in a Complex World PDF Author: Victor Korotkikh
Publisher:
ISBN: 9780387886657
Category : Mathematical optimization
Languages : en
Pages : 325

Get Book Here

Book Description
As complex systems play an increasingly important role in human activities, optimisation becomes a critical issue. This book suggests a new perspective to the problem by recognising the possibility of a general optimality condition that determines the optimal performance of a complex system.

Handbook of Optimization in Complex Networks

Handbook of Optimization in Complex Networks PDF Author: My T. Thai
Publisher: Springer Science & Business Media
ISBN: 1461408571
Category : Mathematics
Languages : en
Pages : 539

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Book Description
Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

Optimization Techniques for Solving Complex Problems

Optimization Techniques for Solving Complex Problems PDF Author: Enrique Alba
Publisher: John Wiley & Sons
ISBN: 0470293322
Category : Computers
Languages : en
Pages : 500

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Book Description
Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real-world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics. Part One—covers methodologies for complex problem solving including genetic programming, neural networks, genetic algorithms, hybrid evolutionary algorithms, and more. Part Two—delves into applications including DNA sequencing and reconstruction, location of antennae in telecommunication networks, metaheuristics, FPGAs, problems arising in telecommunication networks, image processing, time series prediction, and more. All chapters contain examples that illustrate the applications themselves as well as the actual performance of the algorithms.?Optimization Techniques for Solving Complex Problems is a valuable resource for practitioners and researchers who work with optimization in real-world settings.

Optimization of Complex Systems: Theory, Models, Algorithms and Applications

Optimization of Complex Systems: Theory, Models, Algorithms and Applications PDF Author: Hoai An Le Thi
Publisher: Springer
ISBN: 3030218031
Category : Technology & Engineering
Languages : en
Pages : 1164

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Book Description
This book contains 112 papers selected from about 250 submissions to the 6th World Congress on Global Optimization (WCGO 2019) which takes place on July 8–10, 2019 at University of Lorraine, Metz, France. The book covers both theoretical and algorithmic aspects of Nonconvex Optimization, as well as its applications to modeling and solving decision problems in various domains. It is composed of 10 parts, each of them deals with either the theory and/or methods in a branch of optimization such as Continuous optimization, DC Programming and DCA, Discrete optimization & Network optimization, Multiobjective programming, Optimization under uncertainty, or models and optimization methods in a specific application area including Data science, Economics & Finance, Energy & Water management, Engineering systems, Transportation, Logistics, Resource allocation & Production management. The researchers and practitioners working in Nonconvex Optimization and several application areas can find here many inspiring ideas and useful tools & techniques for their works.

Complexity In Numerical Optimization

Complexity In Numerical Optimization PDF Author: Panos M Pardalos
Publisher: World Scientific
ISBN: 9814504084
Category : Mathematics
Languages : en
Pages : 538

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Book Description
Computational complexity, originated from the interactions between computer science and numerical optimization, is one of the major theories that have revolutionized the approach to solving optimization problems and to analyzing their intrinsic difficulty.The main focus of complexity is the study of whether existing algorithms are efficient for the solution of problems, and which problems are likely to be tractable.The quest for developing efficient algorithms leads also to elegant general approaches for solving optimization problems, and reveals surprising connections among problems and their solutions.This book is a collection of articles on recent complexity developments in numerical optimization. The topics covered include complexity of approximation algorithms, new polynomial time algorithms for convex quadratic minimization, interior point algorithms, complexity issues regarding test generation of NP-hard problems, complexity of scheduling problems, min-max, fractional combinatorial optimization, fixed point computations and network flow problems.The collection of articles provide a broad spectrum of the direction in which research is going and help to elucidate the nature of computational complexity in optimization. The book will be a valuable source of information to faculty, students and researchers in numerical optimization and related areas.

Pyomo – Optimization Modeling in Python

Pyomo – Optimization Modeling in Python PDF Author: William E. Hart
Publisher: Springer Science & Business Media
ISBN: 146143226X
Category : Mathematics
Languages : en
Pages : 245

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Book Description
This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. The text illustrates the breadth of the modeling and analysis capabilities that are supported by the software and support of complex real-world applications. Pyomo is an open source software package for formulating and solving large-scale optimization and operations research problems. The text begins with a tutorial on simple linear and integer programming models. A detailed reference of Pyomo's modeling components is illustrated with extensive examples, including a discussion of how to load data from data sources like spreadsheets and databases. Chapters describing advanced modeling capabilities for nonlinear and stochastic optimization are also included. The Pyomo software provides familiar modeling features within Python, a powerful dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions. The software supports a different modeling approach than commercial AML (Algebraic Modeling Languages) tools, and is designed for flexibility, extensibility, portability, and maintainability but also maintains the central ideas in modern AMLs.

Convex Optimization

Convex Optimization PDF Author: Stephen P. Boyd
Publisher: Cambridge University Press
ISBN: 9780521833783
Category : Business & Economics
Languages : en
Pages : 744

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Book Description
Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Engineering Optimization

Engineering Optimization PDF Author: R. Russell Rhinehart
Publisher: John Wiley & Sons
ISBN: 1118936337
Category : Technology & Engineering
Languages : en
Pages : 769

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Book Description
An Application-Oriented Introduction to Essential Optimization Concepts and Best Practices Optimization is an inherent human tendency that gained new life after the advent of calculus; now, as the world grows increasingly reliant on complex systems, optimization has become both more important and more challenging than ever before. Engineering Optimization provides a practically-focused introduction to modern engineering optimization best practices, covering fundamental analytical and numerical techniques throughout each stage of the optimization process. Although essential algorithms are explained in detail, the focus lies more in the human function: how to create an appropriate objective function, choose decision variables, identify and incorporate constraints, define convergence, and other critical issues that define the success or failure of an optimization project. Examples, exercises, and homework throughout reinforce the author’s “do, not study” approach to learning, underscoring the application-oriented discussion that provides a deep, generic understanding of the optimization process that can be applied to any field. Providing excellent reference for students or professionals, Engineering Optimization: Describes and develops a variety of algorithms, including gradient based (such as Newton’s, and Levenberg-Marquardt), direct search (such as Hooke-Jeeves, Leapfrogging, and Particle Swarm), along with surrogate functions for surface characterization Provides guidance on optimizer choice by application, and explains how to determine appropriate optimizer parameter values Details current best practices for critical stages of specifying an optimization procedure, including decision variables, defining constraints, and relationship modeling Provides access to software and Visual Basic macros for Excel on the companion website, along with solutions to examples presented in the book Clear explanations, explicit equation derivations, and practical examples make this book ideal for use as part of a class or self-study, assuming a basic understanding of statistics, calculus, computer programming, and engineering models. Anyone seeking best practices for “making the best choices” will find value in this introductory resource.

Optimization Techniques for Solving Complex Problems

Optimization Techniques for Solving Complex Problems PDF Author: Enrique Alba
Publisher: John Wiley & Sons
ISBN: 9780470411346
Category : Computers
Languages : en
Pages : 504

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Book Description
Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real-world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics. Part One—covers methodologies for complex problem solving including genetic programming, neural networks, genetic algorithms, hybrid evolutionary algorithms, and more. Part Two—delves into applications including DNA sequencing and reconstruction, location of antennae in telecommunication networks, metaheuristics, FPGAs, problems arising in telecommunication networks, image processing, time series prediction, and more. All chapters contain examples that illustrate the applications themselves as well as the actual performance of the algorithms.?Optimization Techniques for Solving Complex Problems is a valuable resource for practitioners and researchers who work with optimization in real-world settings.

Visualization and Optimization

Visualization and Optimization PDF Author: Christopher V. Jones
Publisher: Springer Science & Business Media
ISBN: 9780792396727
Category : Business & Economics
Languages : en
Pages : 458

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Book Description
This book examines ongoing research and practice in using visualization to represent optimization models, explore optimum solutions, and summarize the results of the optimization effort. As research in optimization develops more powerful algorithms capable of analyzing ever more complicated problems, an increasing number of excellent books have been written to explain how to construct optimization models and how to build algorithms to analyze these models. However, solving problems using optimization techniques involves more than just developing newer, faster algorithms. Building, debugging, validating and understanding models and algorithms requires appropriate representations. This book describes how scientific visualization can enhance the representations needed for optimization. Although books on visualization exist, none of them have specifically addressed how visualization can contribute to optimization practice and research. In this book, relevant techniques of computer graphics, virtual reality, sonification, among others, are examined and specifically targeted to optimization. Moreover, applications of optimization to visualization are also explored.