Evolutionary Multiobjective Optimization With Gaussian Process Models
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Evolutionary Multiobjective Optimization With Gaussian Process Models
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Author : Mlakar Miha
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2015-07-20
Evolutionary Multiobjective Optimization With Gaussian Process Models written by Mlakar Miha and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-20 with categories.
This book focuses on the field of surrogate-model-based multiobjective evolutionary optimization. It describes the sate-of-the-art concepts and methods, presents various optimization problems and describes current challenges. The main contributions are done for the optimization problems, where solutions are presented with uncertainty. To compare solutions under uncertainty and improve the optimization results the new relations for comparing solutions under uncertainty are defined. These relations reduce the possibility of incorrect comparisons due to the inaccurate approximations. The relations under uncertainty are then used in the new surrogate-model-based multiobjective evolutionary algorithm called GP-DEMO. The algorithm is thoroughly tested on benchmark and real-world problems and the results show that GP-DEMO, in comparison to other multiobjective evolutionary algorithms, produces comparable results while requiring fewer exact evaluations of the original objective functions.
Evolutionary Multi Criterion Optimization
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Author : António Gaspar-Cunha
language : en
Publisher: Springer
Release Date : 2015-03-17
Evolutionary Multi Criterion Optimization written by António Gaspar-Cunha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-17 with Mathematics categories.
This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimarães, Portugal in March/April 2015. The 68 revised full papers presented together with 4 plenary talks were carefully reviewed and selected from 90 submissions. The EMO 2015 aims to continue these type of developments, being the papers presented focused in: theoretical aspects, algorithms development, many-objectives optimization, robustness and optimization under uncertainty, performance indicators, multiple criteria decision making and real-world applications.
Evolutionary Multi Criterion Optimization
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Author : Kalyanmoy Deb
language : en
Publisher: Springer
Release Date : 2019-02-28
Evolutionary Multi Criterion Optimization written by Kalyanmoy Deb and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-28 with Computers categories.
This book constitutes the refereed proceedings of the 10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019 held in East Lansing, MI, USA, in March 2019. The 59 revised full papers were carefully reviewed and selected from 76 submissions. The papers are divided into 8 categories, each representing a key area of current interest in the EMO field today. They include theoretical developments, algorithmic developments, issues in many-objective optimization, performance metrics, knowledge extraction and surrogate-based EMO, multi-objective combinatorial problem solving, MCDM and interactive EMO methods, and applications.
Evolutionary Large Scale Multi Objective Optimization And Applications
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Author : Xingyi Zhang
language : en
Publisher: John Wiley & Sons
Release Date : 2024-07-22
Evolutionary Large Scale Multi Objective Optimization And Applications written by Xingyi Zhang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Technology & Engineering categories.
Tackle the most challenging problems in science and engineering with these cutting-edge algorithms Multi-objective optimization problems (MOPs) are those in which more than one objective needs to be optimized simultaneously. As a ubiquitous component of research and engineering projects, these problems are notoriously challenging. In recent years, evolutionary algorithms (EAs) have shown significant promise in their ability to solve MOPs, but challenges remain at the level of large-scale multi-objective optimization problems (LSMOPs), where the number of variables increases and the optimized solution is correspondingly harder to reach. Evolutionary Large-Scale Multi-Objective Optimization and Applications constitutes a systematic overview of EAs and their capacity to tackle LSMOPs. It offers an introduction to both the problem class and the algorithms before delving into some of the cutting-edge algorithms which have been specifically adapted to solving LSMOPs. Deeply engaged with specific applications and alert to the latest developments in the field, it’s a must-read for students and researchers facing these famously complex but crucial optimization problems. The book’s readers will also find: Analysis of multi-optimization problems in fields such as machine learning, network science, vehicle routing, and more Discussion of benchmark problems and performance indicators for LSMOPs Presentation of a new taxonomy of algorithms in the field Evolutionary Large-Scale Multi-Objective Optimization and Applications is ideal for advanced students, researchers, and scientists and engineers facing complex optimization problems.
Evolutionary Multi Criterion Optimization
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Author : Heike Trautmann
language : en
Publisher: Springer
Release Date : 2017-02-17
Evolutionary Multi Criterion Optimization written by Heike Trautmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Computers categories.
This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Münster, Germany in March 2017. The 33 revised full papers presented together with 13 poster presentations were carefully reviewed and selected from 72 submissions. The EMO 2017 aims to discuss all aspects of EMO development and deployment, including theoretical foundations; constraint handling techniques; preference handling techniques; handling of continuous, combinatorial or mixed-integer problems; local search techniques; hybrid approaches; stopping criteria; parallel EMO models; performance evaluation; test functions and benchmark problems; algorithm selection approaches; many-objective optimization; large scale optimization; real-world applications; EMO algorithm implementations.
Evolutionary Multi Criterion Optimization
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Author : Michael Emmerich
language : en
Publisher: Springer Nature
Release Date : 2023-03-09
Evolutionary Multi Criterion Optimization written by Michael Emmerich and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-09 with Computers categories.
This book constitutes the refereed proceedings of the 12th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2022 held in Leiden, The Netherlands, during March 20-24, 2023. The 44 regular papers presented in this book were carefully reviewed and selected from 65 submissions. The papers are divided into the following topical sections: Algorithm Design and Engineering; Machine Learning and Multi-criterion Optimization; Benchmarking and Performance Assessment; Indicator Design and Complexity Analysis; Applications in Real World Domains; and Multi-Criteria Decision Making and Interactive Algorithms..
Evolutionary Multi Criterion Optimization
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Author : Hisao Ishibuchi
language : en
Publisher: Springer Nature
Release Date : 2021-03-24
Evolutionary Multi Criterion Optimization written by Hisao Ishibuchi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-24 with Computers categories.
This book constitutes the refereed proceedings of the 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021 held in Shenzhen, China, in March 2021. The 47 full papers and 14 short papers were carefully reviewed and selected from 120 submissions. The papers are divided into the following topical sections: theory; algorithms; dynamic multi-objective optimization; constrained multi-objective optimization; multi-modal optimization; many-objective optimization; performance evaluations and empirical studies; EMO and machine learning; surrogate modeling and expensive optimization; MCDM and interactive EMO; and applications.
Numerical And Evolutionary Optimization 2018
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Author : Adriana Lara
language : en
Publisher: MDPI
Release Date : 2019-11-19
Numerical And Evolutionary Optimization 2018 written by Adriana Lara and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-19 with Technology & Engineering categories.
This book was established after the 6th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications.
High Performance Simulation Based Optimization
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Author : Thomas Bartz-Beielstein
language : en
Publisher: Springer
Release Date : 2019-06-01
High Performance Simulation Based Optimization written by Thomas Bartz-Beielstein and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-01 with Computers categories.
This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations. As traditional optimization approaches are not applicable per se, combinations of computational intelligence, machine learning, and high-performance computing methods are popular solutions. But finding a suitable method is a challenging task, because numerous approaches have been proposed in this highly dynamic field of research. That’s where this book comes in: It covers both theory and practice, drawing on the real-world insights gained by the contributing authors, all of whom are leading researchers. Given its scope, if offers a comprehensive reference guide for researchers, practitioners, and advanced-level students interested in using computational intelligence and machine learning to solve expensive optimization problems.
Evolutionary And Memetic Computing For Project Portfolio Selection And Scheduling
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Author : Kyle Robert Harrison
language : en
Publisher: Springer Nature
Release Date : 2021-11-13
Evolutionary And Memetic Computing For Project Portfolio Selection And Scheduling written by Kyle Robert Harrison and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-13 with Technology & Engineering categories.
This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times. It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.