Uncertain Multi-Criteria Optimization Problems

Uncertain Multi-Criteria Optimization Problems

Author: Dragan Pamucar

Publisher: MDPI

Published: 2021-09-09

Total Pages: 86

ISBN-13: 3036515747

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Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems.


Book Synopsis Uncertain Multi-Criteria Optimization Problems by : Dragan Pamucar

Download or read book Uncertain Multi-Criteria Optimization Problems written by Dragan Pamucar and published by MDPI. This book was released on 2021-09-09 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems.


Uncertain Multi-Criteria Optimization Problems

Uncertain Multi-Criteria Optimization Problems

Author: Dragan Pamučar

Publisher:

Published: 2021

Total Pages: 86

ISBN-13: 9783036515731

DOWNLOAD EBOOK

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems.


Book Synopsis Uncertain Multi-Criteria Optimization Problems by : Dragan Pamučar

Download or read book Uncertain Multi-Criteria Optimization Problems written by Dragan Pamučar and published by . This book was released on 2021 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems.


Evolutionary Multi-Criterion Optimization

Evolutionary Multi-Criterion Optimization

Author: Carlos A. Coello Coello

Publisher: Springer Science & Business Media

Published: 2005-02-17

Total Pages: 927

ISBN-13: 3540249834

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This book constitutes the refereed proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, held in Guanajuato, Mexico, in March 2005. The 59 revised full papers presented together with 2 invited papers and the summary of a tutorial were carefully reviewed and selected from the 115 papers submitted. The papers are organized in topical sections on algorithm improvements, incorporation of preferences, performance analysis and comparison, uncertainty and noise, alternative methods, and applications in a broad variety of fields.


Book Synopsis Evolutionary Multi-Criterion Optimization by : Carlos A. Coello Coello

Download or read book Evolutionary Multi-Criterion Optimization written by Carlos A. Coello Coello and published by Springer Science & Business Media. This book was released on 2005-02-17 with total page 927 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, held in Guanajuato, Mexico, in March 2005. The 59 revised full papers presented together with 2 invited papers and the summary of a tutorial were carefully reviewed and selected from the 115 papers submitted. The papers are organized in topical sections on algorithm improvements, incorporation of preferences, performance analysis and comparison, uncertainty and noise, alternative methods, and applications in a broad variety of fields.


Combinatorial Optimization Under Uncertainty

Combinatorial Optimization Under Uncertainty

Author: Ritu Arora

Publisher: CRC Press

Published: 2023-05-12

Total Pages: 184

ISBN-13: 1000859851

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This book discusses the basic ideas, underlying principles, mathematical formulations, analysis and applications of the different combinatorial problems under uncertainty and attempts to provide solutions for the same. Uncertainty influences the behaviour of the market to a great extent. Global pandemics and calamities are other factors which affect and augment unpredictability in the market. The intent of this book is to develop mathematical structures for different aspects of allocation problems depicting real life scenarios. The novel methods which are incorporated in practical scenarios under uncertain circumstances include the STAR heuristic approach, Matrix geometric method, Ranking function and Pythagorean fuzzy numbers, to name a few. Distinct problems which are considered in this book under uncertainty include scheduling, cyclic bottleneck assignment problem, bilevel transportation problem, multi-index transportation problem, retrial queuing, uncertain matrix games, optimal production evaluation of cotton in different soil and water conditions, the healthcare sector, intuitionistic fuzzy quadratic programming problem, and multi-objective optimization problem. This book may serve as a valuable reference for researchers working in the domain of optimization for solving combinatorial problems under uncertainty. The contributions of this book may further help to explore new avenues leading toward multidisciplinary research discussions.


Book Synopsis Combinatorial Optimization Under Uncertainty by : Ritu Arora

Download or read book Combinatorial Optimization Under Uncertainty written by Ritu Arora and published by CRC Press. This book was released on 2023-05-12 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the basic ideas, underlying principles, mathematical formulations, analysis and applications of the different combinatorial problems under uncertainty and attempts to provide solutions for the same. Uncertainty influences the behaviour of the market to a great extent. Global pandemics and calamities are other factors which affect and augment unpredictability in the market. The intent of this book is to develop mathematical structures for different aspects of allocation problems depicting real life scenarios. The novel methods which are incorporated in practical scenarios under uncertain circumstances include the STAR heuristic approach, Matrix geometric method, Ranking function and Pythagorean fuzzy numbers, to name a few. Distinct problems which are considered in this book under uncertainty include scheduling, cyclic bottleneck assignment problem, bilevel transportation problem, multi-index transportation problem, retrial queuing, uncertain matrix games, optimal production evaluation of cotton in different soil and water conditions, the healthcare sector, intuitionistic fuzzy quadratic programming problem, and multi-objective optimization problem. This book may serve as a valuable reference for researchers working in the domain of optimization for solving combinatorial problems under uncertainty. The contributions of this book may further help to explore new avenues leading toward multidisciplinary research discussions.


Concepts of Robustness for Uncertain Multi-Objective Optimization

Concepts of Robustness for Uncertain Multi-Objective Optimization

Author:

Publisher:

Published: 2014

Total Pages: 182

ISBN-13:

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In this thesis, several concepts of handling uncertainties in the formulation of mathematical optimization problems are presented. Some of these concepts are extensions of classical concepts of robustness for single objective optimization problems, others are newly introduced concepts particularly developed for the multi-objective setting. Properties of these concepts and algorithms for computing the respective solutions are analyzed. Connections between the concepts are investigated and the connection between multi-objective and set-valued optimization is pointed out and used to develop ne...


Book Synopsis Concepts of Robustness for Uncertain Multi-Objective Optimization by :

Download or read book Concepts of Robustness for Uncertain Multi-Objective Optimization written by and published by . This book was released on 2014 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, several concepts of handling uncertainties in the formulation of mathematical optimization problems are presented. Some of these concepts are extensions of classical concepts of robustness for single objective optimization problems, others are newly introduced concepts particularly developed for the multi-objective setting. Properties of these concepts and algorithms for computing the respective solutions are analyzed. Connections between the concepts are investigated and the connection between multi-objective and set-valued optimization is pointed out and used to develop ne...


Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Author: Thu Bui, Lam

Publisher: IGI Global

Published: 2008-05-31

Total Pages: 496

ISBN-13: 1599045001

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Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.


Book Synopsis Multi-Objective Optimization in Computational Intelligence: Theory and Practice by : Thu Bui, Lam

Download or read book Multi-Objective Optimization in Computational Intelligence: Theory and Practice written by Thu Bui, Lam and published by IGI Global. This book was released on 2008-05-31 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.


Multi-dimensional Control Problems

Multi-dimensional Control Problems

Author: Anurag Jayswal

Publisher: Springer Nature

Published: 2022-10-31

Total Pages: 195

ISBN-13: 9811965617

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This book deals with several types of multi-dimensional control problems in the face of data uncertainty for vector cases—multi-dimensional multi-objective control problem with uncertain objective functionals, uncertain constraint functionals, and uncertain objective as well as constraint functionals, uncertain multi-dimensional multi-objective control problem with semi-infinite constraints, uncertain dual multi-dimensional multi-objective variational control problem, and second-order PDE&PDI constrained robust optimization problem. The book provides the solution approaches—an exact l1 penalty function approach, modified objective approach, robust approach—in the simplest way to solve the recent developing optimization problems in the sense of uncertainty.


Book Synopsis Multi-dimensional Control Problems by : Anurag Jayswal

Download or read book Multi-dimensional Control Problems written by Anurag Jayswal and published by Springer Nature. This book was released on 2022-10-31 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with several types of multi-dimensional control problems in the face of data uncertainty for vector cases—multi-dimensional multi-objective control problem with uncertain objective functionals, uncertain constraint functionals, and uncertain objective as well as constraint functionals, uncertain multi-dimensional multi-objective control problem with semi-infinite constraints, uncertain dual multi-dimensional multi-objective variational control problem, and second-order PDE&PDI constrained robust optimization problem. The book provides the solution approaches—an exact l1 penalty function approach, modified objective approach, robust approach—in the simplest way to solve the recent developing optimization problems in the sense of uncertainty.


Nonlinear Interval Optimization for Uncertain Problems

Nonlinear Interval Optimization for Uncertain Problems

Author: Chao Jiang

Publisher: Springer Nature

Published: 2020-12-08

Total Pages: 291

ISBN-13: 9811585466

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This book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods.


Book Synopsis Nonlinear Interval Optimization for Uncertain Problems by : Chao Jiang

Download or read book Nonlinear Interval Optimization for Uncertain Problems written by Chao Jiang and published by Springer Nature. This book was released on 2020-12-08 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods.


Multi-Objective Optimization

Multi-Objective Optimization

Author: Jyotsna K. Mandal

Publisher: Springer

Published: 2018-08-18

Total Pages: 318

ISBN-13: 9811314713

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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.


Book Synopsis Multi-Objective Optimization by : Jyotsna K. Mandal

Download or read book Multi-Objective Optimization written by Jyotsna K. Mandal and published by Springer. This book was released on 2018-08-18 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Applied Multi-objective Optimization

Applied Multi-objective Optimization

Author: Nilanjan Dey

Publisher: Springer Nature

Published: 2024

Total Pages: 181

ISBN-13: 9819703530

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The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science.


Book Synopsis Applied Multi-objective Optimization by : Nilanjan Dey

Download or read book Applied Multi-objective Optimization written by Nilanjan Dey and published by Springer Nature. This book was released on 2024 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science.