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Author: Xavier Esquivel Publisher: LAP Lambert Academic Publishing ISBN: 9783659184963 Category : Languages : en Pages : 124
Book Description
In this work we deal with the design of archive based multi-objective evolutionary algorithms (MOEAs) for the numerical treatment of multi objective optimization problems (MOPs). In particular, we design two generational operators one mutation and one crossover operator that are tailored to a class of archiving strategies and propose a new evolutionary strategy. Furthermore, we investigate here two widely used indicators for the evaluation of Multi-objective Evolutionary Algorithms, the Generational Distance (GD) and the Inverted Generational Distance (IGD), with respect to the properties of ametric. We de ne a new performance indicator, p, which can be viewed as an 'averaged Hausdor distance' between the outcome set and the Pareto front and which is composed of (slight modi cations of) the well-known indicators Generational Distance (GD) and Inverted Generational Distance (IGD). We will discuss theoretical properties of p (as well as for GD and IGD) such as the metric properties and the compliance with state-of-the-art multi-objective evolutionary algorithms (MOEAs)."
Author: Xavier Esquivel Publisher: LAP Lambert Academic Publishing ISBN: 9783659184963 Category : Languages : en Pages : 124
Book Description
In this work we deal with the design of archive based multi-objective evolutionary algorithms (MOEAs) for the numerical treatment of multi objective optimization problems (MOPs). In particular, we design two generational operators one mutation and one crossover operator that are tailored to a class of archiving strategies and propose a new evolutionary strategy. Furthermore, we investigate here two widely used indicators for the evaluation of Multi-objective Evolutionary Algorithms, the Generational Distance (GD) and the Inverted Generational Distance (IGD), with respect to the properties of ametric. We de ne a new performance indicator, p, which can be viewed as an 'averaged Hausdor distance' between the outcome set and the Pareto front and which is composed of (slight modi cations of) the well-known indicators Generational Distance (GD) and Inverted Generational Distance (IGD). We will discuss theoretical properties of p (as well as for GD and IGD) such as the metric properties and the compliance with state-of-the-art multi-objective evolutionary algorithms (MOEAs)."
Author: Oliver Schütze Publisher: Springer Nature ISBN: 3030637735 Category : Technology & Engineering Languages : en Pages : 242
Book Description
This book presents an overview of archiving strategies developed over the last years by the authors that deal with suitable approximations of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All presented archivers are analyzed with respect to the approximation qualities of the limit archives that they generate and the upper bounds of the archive sizes. The convergence analysis will be done using a very broad framework that involves all existing stochastic search algorithms and that will only use minimal assumptions on the process to generate new candidate solutions. All of the presented archivers can effortlessly be coupled with any set-based multi-objective search algorithm such as multi-objective evolutionary algorithms, and the resulting hybrid method takes over the convergence properties of the chosen archiver. This book hence targets at all algorithm designers and practitioners in the field of multi-objective optimization.
Author: Ajith Abraham Publisher: Springer Science & Business Media ISBN: 1846281377 Category : Computers Languages : en Pages : 313
Book Description
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.
Author: IEEE Staff Publisher: ISBN: 9781728169309 Category : Languages : en Pages :
Book Description
IEEE CEC is the leading event in the field of evolutionary computation, and covers all topics in evolutionary computation from theory to applications
Author: Carlos Coello Coello Publisher: Springer Science & Business Media ISBN: 0387332545 Category : Computers Languages : en Pages : 810
Book Description
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.
Author: Slim Bechikh Publisher: Springer ISBN: 3319429787 Category : Technology & Engineering Languages : en Pages : 187
Book Description
This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.
Author: Ashish Ghosh Publisher: Springer Science & Business Media ISBN: 3642189652 Category : Computers Languages : en Pages : 1001
Book Description
This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.
Author: Robin Purshouse Publisher: Springer ISBN: 364237140X Category : Computers Languages : en Pages : 859
Book Description
This book constitutes the refereed proceedings of the 7th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2013 held in Sheffield, UK, in March 2013. The 57 revised full papers presented were carefully reviewed and selected from 98 submissions. The papers are grouped in topical sections on plenary talks; new horizons; indicator-based methods; aspects of algorithm design; pareto-based methods; hybrid MCDA; decomposition-based methods; classical MCDA; exploratory problem analysis; product and process applications; aerospace and automotive applications; further real-world applications; and under-explored challenges.
Author: Carlos A. Coello Coello Publisher: World Scientific ISBN: 9812561064 Category : Computers Languages : en Pages : 792
Book Description
- Detailed MOEA applications discussed by international experts - State-of-the-art practical insights in tackling statistical optimization with MOEAs - A unique monograph covering a wide spectrum of real-world applications - Step-by-step discussion of MOEA applications in a variety of domains
Author: Kalyanmoy Deb Publisher: John Wiley & Sons ISBN: 9780471873396 Category : Mathematics Languages : en Pages : 540
Book Description
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.
Author: Xavier Esquivel
Author: Xavier Esquivel
Author: Oliver Schütze
Author: Ajith Abraham
Author: IEEE Staff
Author: Carlos Coello Coello
Author: Slim Bechikh
Author: Ashish Ghosh
Author: Robin Purshouse
Author: Carlos A. Coello Coello
Author: Kalyanmoy Deb