Multi Objective Optimization Problems

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Multi-Objective Optimization Problems

Fran Sérgio Lobato,Valder Steffen Jr.
Multi Objective Optimization Problems Book PDF

Author : Fran Sérgio Lobato,Valder Steffen Jr.
Publisher : Springer
Page : 160 pages
File Size : 42,7 Mb
Release : 2017-07-03
Category : Mathematics
ISBN : 9783319585659

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Multi-Objective Optimization Problems by Fran Sérgio Lobato,Valder Steffen Jr. Pdf

This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.

Evolutionary Algorithms for Solving Multi-Objective Problems

Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Evolutionary Algorithms for Solving Multi Objective Problems Book PDF

Author : Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Publisher : Springer Science & Business Media
Page : 810 pages
File Size : 55,7 Mb
Release : 2007-08-26
Category : Computers
ISBN : 9780387367972

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Evolutionary Algorithms for Solving Multi-Objective Problems by Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen Pdf

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Multiobjective Optimization

Yann Collette,Patrick Siarry
Multiobjective Optimization Book PDF

Author : Yann Collette,Patrick Siarry
Publisher : Springer Science & Business Media
Page : 290 pages
File Size : 52,6 Mb
Release : 2013-06-29
Category : Mathematics
ISBN : 9783662088838

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Multiobjective Optimization by Yann Collette,Patrick Siarry Pdf

This text offers many multiobjective optimization methods accompanied by analytical examples, and it treats problems not only in engineering but also operations research and management. It explains how to choose the best method to solve a problem and uses three primary application examples: optimization of the numerical simulation of an industrial process; sizing of a telecommunication network; and decision-aid tools for the sorting of bids.

Multi-Objective Optimization

Jyotsna K. Mandal,Somnath Mukhopadhyay,Paramartha Dutta
Multi Objective Optimization Book PDF

Author : Jyotsna K. Mandal,Somnath Mukhopadhyay,Paramartha Dutta
Publisher : Springer
Page : 318 pages
File Size : 49,7 Mb
Release : 2018-08-18
Category : Computers
ISBN : 9789811314711

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Multi-Objective Optimization by Jyotsna K. Mandal,Somnath Mukhopadhyay,Paramartha Dutta Pdf

This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.

Multi-Objective Optimization using Artificial Intelligence Techniques

Seyedali Mirjalili,Jin Song Dong
Multi Objective Optimization using Artificial Intelligence Techniques Book PDF

Author : Seyedali Mirjalili,Jin Song Dong
Publisher : Springer
Page : 58 pages
File Size : 53,7 Mb
Release : 2019-07-24
Category : Technology & Engineering
ISBN : 9783030248352

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Multi-Objective Optimization using Artificial Intelligence Techniques by Seyedali Mirjalili,Jin Song Dong Pdf

This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

Multiobjective Optimization

Jürgen Branke,Kalyanmoy Deb,Kaisa Miettinen,Roman Slowiński
Multiobjective Optimization Book PDF

Author : Jürgen Branke,Kalyanmoy Deb,Kaisa Miettinen,Roman Slowiński
Publisher : Springer
Page : 470 pages
File Size : 44,6 Mb
Release : 2008-10-18
Category : Computers
ISBN : 9783540889083

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Multiobjective Optimization by Jürgen Branke,Kalyanmoy Deb,Kaisa Miettinen,Roman Slowiński Pdf

Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.

Multi-Objective Combinatorial Optimization Problems and Solution Methods

Mehdi Toloo,Siamak Talatahari,Iman Rahimi
Multi Objective Combinatorial Optimization Problems and Solution Methods Book PDF

Author : Mehdi Toloo,Siamak Talatahari,Iman Rahimi
Publisher : Academic Press
Page : 316 pages
File Size : 46,8 Mb
Release : 2022-02-09
Category : Science
ISBN : 9780128238004

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Multi-Objective Combinatorial Optimization Problems and Solution Methods by Mehdi Toloo,Siamak Talatahari,Iman Rahimi Pdf

Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice. Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms

Multiobjective Optimization: Behavioral and Computational Considerations

Jeffrey L. Ringuest
Multiobjective Optimization Behavioral and Computational Considerations Book PDF

Author : Jeffrey L. Ringuest
Publisher : Springer Science & Business Media
Page : 178 pages
File Size : 52,7 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9781461536123

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Multiobjective Optimization: Behavioral and Computational Considerations by Jeffrey L. Ringuest Pdf

Throughout the development of mathematical programming researchers have paid great attention to problems that are described by a single objective that can only be achieved subject to satisfying a set of restrictions or constraints. Recently, it has been recognized that the use of a single objective limits the applicability of In reality, many multiobjective mathematical programming models. situations exist and frequently these mUltiple objectives are in direct conflict. Research on multiobjective problems can be broken down into two broad categories: multiobjective optimization and multicriterion decision theory. Multiobjective optimization models are based on techniques such as linear programming. In general, the multiobjective optimization problem can be defined as finding a feasible alternative that yields the most preferred set of values for the objective functions. This problem differs from a single objective because subjective methods are required to determine which alternative is most preferred. A body of literature parallel to that m multiobjective optimization has been developing in the area of multicriterion decision theory. These models are based on classical decision analysis, particularly utility theory. One focus of this research has been the development and testing of procedures for estimating multiattribute utility functions that are consistent with rational decision maker behavior. A utility function provides a model of a decision maker's choice among alternatives. This literature is directly xii MULTIOBJECTIVE OPTIMIZATION applicable to multiobjective optimization and provides much needed insight into the subjective character of that problem.

Multi-Objective Optimization using Evolutionary Algorithms

Kalyanmoy Deb
Multi Objective Optimization using Evolutionary Algorithms Book PDF

Author : Kalyanmoy Deb
Publisher : John Wiley & Sons
Page : 540 pages
File Size : 43,5 Mb
Release : 2001-07-05
Category : Mathematics
ISBN : 047187339X

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Multi-Objective Optimization using Evolutionary Algorithms by Kalyanmoy Deb Pdf

Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Geboten werden alle notwendigen Grundlagen, um die Theorie auf Probleme der Ingenieurtechnik, der Vorhersage und der Planung anzuwenden. Der Autor gibt auch einen Ausblick auf Forschungsaufgaben der Zukunft.

Evolutionary Multiobjective Optimization

Ajith Abraham,Robert Goldberg
Evolutionary Multiobjective Optimization Book PDF

Author : Ajith Abraham,Robert Goldberg
Publisher : Springer Science & Business Media
Page : 313 pages
File Size : 51,9 Mb
Release : 2005-09-05
Category : Computers
ISBN : 9781846281372

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Evolutionary Multiobjective Optimization by Ajith Abraham,Robert Goldberg Pdf

Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.

Search Methodologies

Edmund K. Burke,Graham Kendall
Search Methodologies Book PDF

Author : Edmund K. Burke,Graham Kendall
Publisher : Springer Science & Business Media
Page : 715 pages
File Size : 52,7 Mb
Release : 2013-10-18
Category : Business & Economics
ISBN : 9781461469407

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Search Methodologies by Edmund K. Burke,Graham Kendall Pdf

The first edition of Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques was originally put together to offer a basic introduction to the various search and optimization techniques that students might need to use during their research, and this new edition continues this tradition. Search Methodologies has been expanded and brought completely up to date, including new chapters covering scatter search, GRASP, and very large neighborhood search. The chapter authors are drawn from across Computer Science and Operations Research and include some of the world’s leading authorities in their field. The book provides useful guidelines for implementing the methods and frameworks described and offers valuable tutorials to students and researchers in the field. “As I embarked on the pleasant journey of reading through the chapters of this book, I became convinced that this is one of the best sources of introductory material on the search methodologies topic to be found. The book’s subtitle, “Introductory Tutorials in Optimization and Decision Support Techniques”, aptly describes its aim, and the editors and contributors to this volume have achieved this aim with remarkable success. The chapters in this book are exemplary in giving useful guidelines for implementing the methods and frameworks described.” Fred Glover, Leeds School of Business, University of Colorado Boulder, USA “[The book] aims to present a series of well written tutorials by the leading experts in their fields. Moreover, it does this by covering practically the whole possible range of topics in the discipline. It enables students and practitioners to study and appreciate the beauty and the power of some of the computational search techniques that are able to effectively navigate through search spaces that are sometimes inconceivably large. I am convinced that this second edition will build on the success of the first edition and that it will prove to be just as popular.” Jacek Blazewicz, Institute of Computing Science, Poznan University of Technology and Institute of Bioorganic Chemistry, Polish Academy of Sciences

Parallel Problem Solving from Nature - PPSN VIII

Xin Yao
Parallel Problem Solving from Nature PPSN VIII Book PDF

Author : Xin Yao
Publisher : Springer Science & Business Media
Page : 1204 pages
File Size : 53,7 Mb
Release : 2004-09-13
Category : Computers
ISBN : 9783540230922

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Parallel Problem Solving from Nature - PPSN VIII by Xin Yao Pdf

This book constitutes the refereed proceedings of the 8th International Conference on Parallel Problem Solving from Nature, PPSN 2004, held in Birmingham, UK, in September 2004. The 119 revised full papers presented were carefully reviewed and selected from 358 submissions. The papers address all current issues in biologically inspired computing; they are organized in topical sections on theoretical and foundational issues, new algorithms, applications, multi-objective optimization, co-evolution, robotics and multi-agent systems, and learning classifier systems and data mining.

Multi-Objective Optimization in Computer Networks Using Metaheuristics

Yezid Donoso,Ramon Fabregat
Multi Objective Optimization in Computer Networks Using Metaheuristics Book PDF

Author : Yezid Donoso,Ramon Fabregat
Publisher : CRC Press
Page : 472 pages
File Size : 41,5 Mb
Release : 2016-04-19
Category : Computers
ISBN : 9781420013627

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Multi-Objective Optimization in Computer Networks Using Metaheuristics by Yezid Donoso,Ramon Fabregat Pdf

Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design an

Non-Convex Multi-Objective Optimization

Panos M. Pardalos,Antanas Žilinskas,Julius Žilinskas
Non Convex Multi Objective Optimization Book PDF

Author : Panos M. Pardalos,Antanas Žilinskas,Julius Žilinskas
Publisher : Springer
Page : 196 pages
File Size : 53,6 Mb
Release : 2017-07-27
Category : Mathematics
ISBN : 9783319610078

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Non-Convex Multi-Objective Optimization by Panos M. Pardalos,Antanas Žilinskas,Julius Žilinskas Pdf

Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.

Multi-Objective Optimization in Theory and Practice II: Metaheuristic Algorithms

André A. Keller
Multi Objective Optimization in Theory and Practice II Metaheuristic Algorithms Book PDF

Author : André A. Keller
Publisher : Bentham Science Publishers
Page : 310 pages
File Size : 48,5 Mb
Release : 2019-03-28
Category : Mathematics
ISBN : 9781681087061

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Multi-Objective Optimization in Theory and Practice II: Metaheuristic Algorithms by André A. Keller Pdf

Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of solutions, metaheuristic algorithms, genetic search algorithms and evolution strategies, decomposition algorithms, hybridization of different metaheuristics, and many-objective (more than three objectives) optimization and parallel computation. The final section of the book presents information about the design and types of fifty test problems for which the Pareto-optimal front is approximated. For each of them, the package NSGA-II is used to approximate the Pareto-optimal front. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science and mathematics degree programs.