Evolutionary Multi Criterion Optimization

Author: Carlos M. Fonseca
Editor: Springer
ISBN: 3540369708
File Size: 65,36 MB
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This book constitutes the refereed proceedings of the Second International Conference on Evolutionary Multi-Criterion Optimization, EMO 2003, held in Faro, Portugal, in April 2003. The 56 revised full papers presented were carefully reviewed and selected from a total of 100 submissions. The papers are organized in topical sections on objective handling and problem decomposition, algorithm improvements, online adaptation, problem construction, performance analysis and comparison, alternative methods, implementation, and applications.

Evolutionary Multi Criterion Optimization

Author: Matthias Ehrgott
Editor: Springer Science & Business Media
ISBN: 3642010199
File Size: 16,36 MB
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Multi-criterionoptimizationreferstooptimizationproblemswithtwoormore- jectives expressing con?icting goals that are formulated within a mathematical programming framework. The problems addressed may involve linear or nonl- ear objective functions and/or constraints, continuous or discrete variables, and may or may not be a?ected by uncertainty in the data. This branch of multiple criteria decision making (MCDM) ?nds application in numerous domains: en- neering design, health, transportation,telecommunications, bioinformatics, etc. The concept of a unique optimal solution does not apply as soon as multiple objectives are optimized simultaneously. The models and methods introduced in multi-criterion optimization deal with the concept of a set of e?cient (also called Pareto optimal) solutions. E?cient solutions imply trade-o?s between the di?erentcriteria. Thecomputationofthee?cientsolutionsetmaybehardwhen the size of the problem is large, when the problem is computationally complex, when the data are not crisp. It is then often impossible to guarantee the com- tation of exact solutions. In that case, approximate solutions, i. e. , sub-optimal solutionscomputedwithlimitedandcontrolledresources,suchasavailabletime, are of interest. This is the domain of multi-objective metaheuristics, of which evolutionary multi-criterion optimization (EMO) is de?nitely the most pro- nent representative. The success of EMO is due to the simplicity of its concepts and the generality of its methods, and is clearly expressed by the many impr- sive success stories reported in the literature. Research activities in EMO have boomed since the mid-1990s. Three g- erations of work are identi?able throughout the years.

Evolutionary Multi Criterion Optimization

Author: Carlos Coello Coello
Editor: Springer
ISBN: 3540318801
File Size: 12,35 MB
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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.

Evolutionary Multi Criterion Optimization

Author: Eckart Zitzler
Editor: Springer
ISBN: 3540447199
File Size: 59,96 MB
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This book constitutes the refereed proceedings of the First International Conference on Multi-Criterion Optimization, EMO 2001, held in Zurich, Switzerland in March 2001. The 45 revised full papers presented were carefully reviewed and selected from a total of 87 submissions. Also included are two tutorial surveys and two invited papers. The book is organized in topical sections on algorithm improvements, performance assessment and comparison, constraint handling and problem decomposition, uncertainty and noise, hybrid and alternative methods, scheduling, and applications of multi-objective optimization in a variety of fields.

Evolutionary Multi Criterion Optimization

Author: Hisao Ishibuchi
Editor: Springer Nature
ISBN: 3030720624
File Size: 35,56 MB
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Evolutionary Multi Criterion Optimization

Author: António Gaspar-Cunha
Editor: Springer
ISBN: 3319158929
File Size: 56,90 MB
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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

Author: Kalyanmoy Deb
Editor: Springer
ISBN: 303012598X
File Size: 45,39 MB
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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 Multi Criterion Optimization

Author: Robin Purshouse
Editor: Springer
ISBN: 364237140X
File Size: 25,26 MB
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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.

Evolutionary Multi Criterion Optimization

Author: Shigeru Obayashi
Editor: Springer Science & Business Media
ISBN: 3540709274
File Size: 56,28 MB
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This book constitutes the refereed proceedings of the 4th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007, held in Matsushima, Japan in March 2007. The 65 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 124 submissions. The papers are organized in topical sections on algorithm design, algorithm improvements, alternative methods, applications, engineering design, many objectives, objective handling, and performance assessments.

Evolutionary Multi Criterion Optimization

Author: Heike Trautmann
Editor: Springer
ISBN: 3319541579
File Size: 28,19 MB
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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

Author:
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ISBN:
File Size: 44,49 MB
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Evolutionary Multi Objective System Design

Author: Nadia Nedjah
Editor: CRC Press
ISBN: 1498780296
File Size: 48,73 MB
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Real-world engineering problems often require concurrent optimization of several design objectives, which are conflicting in cases. This type of optimization is generally called multi-objective or multi-criterion optimization. The area of research that applies evolutionary methodologies to multi-objective optimization is of special and growing interest. It brings a viable computational solution to many real-world problems. Generally, multi-objective engineering problems do not have a straightforward optimal design. These kinds of problems usually inspire several solutions of equal efficiency, which achieve different trade-offs. Decision makers’ preferences are normally used to select the most adequate design. Such preferences may be dictated before or after the optimization takes place. They may also be introduced interactively at different levels of the optimization process. Multi-objective optimization methods can be subdivided into classical and evolutionary. The classical methods usually aim at a single solution while the evolutionary methods provide a whole set of so-called Pareto-optimal solutions. Evolutionary Multi-Objective System Design: Theory and Applications provides a representation of the state-of-the-art in evolutionary multi-objective optimization research area and related new trends. It reports many innovative designs yielded by the application of such optimization methods. It also presents the application of multi-objective optimization to the following problems: Embrittlement of stainless steel coated electrodes Learning fuzzy rules from imbalanced datasets Combining multi-objective evolutionary algorithms with collective intelligence Fuzzy gain scheduling control Smart placement of roadside units in vehicular networks Combining multi-objective evolutionary algorithms with quasi-simplex local search Design of robust substitution boxes Protein structure prediction problem Core assignment for efficient network-on-chip-based system design

Multiobjective Optimization

Author: Jürgen Branke
Editor: Springer Science & Business Media
ISBN: 3540889078
File Size: 20,43 MB
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Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Based on the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, this book gives an account of the status of research and applications in this field.

Real World Multi Objective System Engineering

Author: Nadia Nedjah
Editor: Nova Publishers
ISBN: 9781594543906
File Size: 69,13 MB
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Real-world engineering problems often require concurrent optimisation of several design objectives, which are conflicting in most of the cases. Such an optimisation is generally called multi-objective or multi-criterion optimisation. The area of research that applies evolutionary methodologies to multi-objective optimisation is of special and growing interest. It brings a solution to many yet-opened real-world problems and questions. Generally, multi-objective engineering problems have no single optimal design, but several solutions of equal efficiency allowing different trade-offs. The decision maker's preferences are normally used to select the most adequate design. Such preferences may be dictated before or after the optimisation takes place. They may also be introduced interactively at different levels of the optimisation process. Multi-objective optimisation methods can be subdivided into classical and evolutionary. The classical methods usually aim at a single solution while the evolutionary methods target a whole set of so-called Pareto-optimal solutions. The aim of this book is to provide a representation of the state-of-the-art of the evolutionary multi-objective optimisation research area and related new trends. Furthermore, it reports many innovative designs yielded by the application of such optimisation methods. The contents of the book are divided into two main parts: evolutionary multi-objective optimisation and evolutionary multi-objective designs.

Multi Objective Evolutionary Optimisation For Product Design And Manufacturing

Author: Lihui Wang
Editor: Springer Science & Business Media
ISBN: 9780857296528
File Size: 76,24 MB
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With the increasing complexity and dynamism in today’s product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make Multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.

Multi Objective Optimization Using Evolutionary Algorithms

Author: Kalyanmoy Deb
Editor: John Wiley & Sons
ISBN: 9780471873396
File Size: 16,10 MB
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Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and in-depth discussion Includes many applications to real-world problems, including engineering design and scheduling Includes discussion of advanced topics and future research Can be used as a course text or for self-study Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.