Metaheuristics For Multiobjective Optimisation

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Metaheuristics for Multiobjective Optimisation

Xavier Gandibleux,Marc Sevaux,Kenneth Sörensen,Vincent T'Kindt
Metaheuristics for Multiobjective Optimisation Book PDF

Author : Xavier Gandibleux,Marc Sevaux,Kenneth Sörensen,Vincent T'Kindt
Publisher : Springer Science & Business Media
Page : 252 pages
File Size : 52,8 Mb
Release : 2012-08-27
Category : Mathematics
ISBN : 9783642171444

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Metaheuristics for Multiobjective Optimisation by Xavier Gandibleux,Marc Sevaux,Kenneth Sörensen,Vincent T'Kindt Pdf

The success of metaheuristics on hard single-objective optimization problems is well recognized today. However, many real-life problems require taking into account several conflicting points of view corresponding to multiple objectives. The use of metaheuristic optimization techniques for multi-objective problems is the subject of this volume. The book includes selected surveys, tutorials and state-of-the-art research papers in this field, which were first presented at a free workshop jointly organized by the French working group on Multi-objective Mathematical Programming (PM2O) and the EURO working group on Metaheuristics in December 2002. It is the first book which considers both various metaheuristics and various kind of problems (e.g. combinatorial problems, real situations, non-linear problems) applied to multiple objective optimization. Metaheuristics used include: genetic algorithms, ant colony optimization, simulated annealing, scatter search, etc. Problems concern timetabling, vehicle routing, and more. Methodological aspects, such as quality evaluation, are also covered.

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 : 51,8 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.

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 : 48,8 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

Advances in Metaheuristics for Hard Optimization

Patrick Siarry,Zbigniew Michalewicz
Advances in Metaheuristics for Hard Optimization Book PDF

Author : Patrick Siarry,Zbigniew Michalewicz
Publisher : Springer Science & Business Media
Page : 484 pages
File Size : 52,5 Mb
Release : 2007-12-06
Category : Mathematics
ISBN : 9783540729600

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Advances in Metaheuristics for Hard Optimization by Patrick Siarry,Zbigniew Michalewicz Pdf

Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.

Discrete Diversity and Dispersion Maximization

Rafael Martí,Anna Martínez-Gavara
Discrete Diversity and Dispersion Maximization Book PDF

Author : Rafael Martí,Anna Martínez-Gavara
Publisher : Springer Nature
Page : 350 pages
File Size : 47,7 Mb
Release : 2024-01-06
Category : Mathematics
ISBN : 9783031383106

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Discrete Diversity and Dispersion Maximization by Rafael Martí,Anna Martínez-Gavara Pdf

This book demonstrates the metaheuristic methodologies that apply to maximum diversity problems to solve them. Maximum diversity problems arise in many practical settings from facility location to social network analysis and constitute an important class of NP-hard problems in combinatorial optimization. In fact, this volume presents a “missing link” in the combinatorial optimization-related literature. In providing the basic principles and fundamental ideas of the most successful methodologies for discrete optimization, this book allows readers to create their own applications for other discrete optimization problems. Additionally, the book is designed to be useful and accessible to researchers and practitioners in management science, industrial engineering, economics, and computer science, while also extending value to non-experts in combinatorial optimization. Owed to the tutorials presented in each chapter, this book may be used in a master course, a doctoral seminar, or as supplementary to a primary text in upper undergraduate courses. The chapters are divided into three main sections. The first section describes a metaheuristic methodology in a tutorial style, offering generic descriptions that, when applied, create an implementation of the methodology for any optimization problem. The second section presents the customization of the methodology to a given diversity problem, showing how to go from theory to application in creating a heuristic. The final part of the chapters is devoted to experimentation, describing the results obtained with the heuristic when solving the diversity problem. Experiments in the book target the so-called MDPLIB set of instances as a benchmark to evaluate the performance of the methods.

Metaheuristics for Combinatorial Optimization

Salvatore Greco,Mario F. Pavone,El-Ghazali Talbi,Daniele Vigo
Metaheuristics for Combinatorial Optimization Book PDF

Author : Salvatore Greco,Mario F. Pavone,El-Ghazali Talbi,Daniele Vigo
Publisher : Springer Nature
Page : 69 pages
File Size : 45,7 Mb
Release : 2021-02-13
Category : Technology & Engineering
ISBN : 9783030685201

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Metaheuristics for Combinatorial Optimization by Salvatore Greco,Mario F. Pavone,El-Ghazali Talbi,Daniele Vigo Pdf

This book presents novel and original metaheuristics developed to solve the cost-balanced traveling salesman problem. This problem was taken into account for the Metaheuristics Competition proposed in MESS 2018, Metaheuristics Summer School, and the top 4 methodologies ranked are included in the book, together with a brief introduction to the traveling salesman problem and all its variants. The book is aimed particularly at all researchers in metaheuristics and combinatorial optimization areas. Key uses are metaheuristics; complex problem solving; combinatorial optimization; traveling salesman problem.

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance

Vasant, Pandian M.
Meta Heuristics Optimization Algorithms in Engineering Business Economics and Finance Book PDF

Author : Vasant, Pandian M.
Publisher : IGI Global
Page : 735 pages
File Size : 46,5 Mb
Release : 2012-09-30
Category : Computers
ISBN : 9781466620872

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Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance by Vasant, Pandian M. Pdf

Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

Recent Developments in Metaheuristics

Lionel Amodeo,El-Ghazali Talbi,Farouk Yalaoui
Recent Developments in Metaheuristics Book PDF

Author : Lionel Amodeo,El-Ghazali Talbi,Farouk Yalaoui
Publisher : Springer
Page : 496 pages
File Size : 55,9 Mb
Release : 2017-09-18
Category : Business & Economics
ISBN : 9783319582535

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Recent Developments in Metaheuristics by Lionel Amodeo,El-Ghazali Talbi,Farouk Yalaoui Pdf

This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.

Hybrid Metaheuristics

El-ghazali Talbi
Hybrid Metaheuristics Book PDF

Author : El-ghazali Talbi
Publisher : Springer
Page : 464 pages
File Size : 55,7 Mb
Release : 2012-07-31
Category : Technology & Engineering
ISBN : 9783642306716

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Hybrid Metaheuristics by El-ghazali Talbi Pdf

The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.

Advances in Metaheuristics

Luca Di Gaspero,Andrea Schaerf,Thomas Stützle
Advances in Metaheuristics Book PDF

Author : Luca Di Gaspero,Andrea Schaerf,Thomas Stützle
Publisher : Springer Science & Business Media
Page : 193 pages
File Size : 53,5 Mb
Release : 2013-03-01
Category : Business & Economics
ISBN : 9781461463221

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Advances in Metaheuristics by Luca Di Gaspero,Andrea Schaerf,Thomas Stützle Pdf

Metaheuristics have been a very active research topic for more than two decades. During this time many new metaheuristic strategies have been devised, they have been experimentally tested and improved on challenging benchmark problems, and they have proven to be important tools for tackling optimization tasks in a large number of practical applications. In other words, metaheuristics are nowadays established as one of the main search paradigms for tackling computationally hard problems. Still, there are a large number of research challenges in the area of metaheuristics. These challenges range from more fundamental questions on theoretical properties and performance guarantees, empirical algorithm analysis, the effective configuration of metaheuristic algorithms, approaches to combine metaheuristics with other algorithmic techniques, towards extending the available techniques to tackle ever more challenging problems. This edited volume grew out of the contributions presented at the ninth Metaheuristics International Conference that was held in Udine, Italy, 25-28 July 2011. The conference comprised 117 presentations of peer-reviewed contributions and 3 invited talks, and it has been attended by 169 delegates. The chapters that are collected in this book exemplify contributions to several of the research directions outlined above.

Metaheuristics for Big Data

Clarisse Dhaenens,Laetitia Jourdan
Metaheuristics for Big Data Book PDF

Author : Clarisse Dhaenens,Laetitia Jourdan
Publisher : John Wiley & Sons
Page : 212 pages
File Size : 47,8 Mb
Release : 2016-08-16
Category : Computers
ISBN : 9781119347583

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Metaheuristics for Big Data by Clarisse Dhaenens,Laetitia Jourdan Pdf

Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.

Optimization Using Evolutionary Algorithms and Metaheuristics

Kaushik Kumar,J. Paulo Davim
Optimization Using Evolutionary Algorithms and Metaheuristics Book PDF

Author : Kaushik Kumar,J. Paulo Davim
Publisher : CRC Press
Page : 138 pages
File Size : 54,6 Mb
Release : 2019-08-22
Category : Technology & Engineering
ISBN : 9781000546804

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Optimization Using Evolutionary Algorithms and Metaheuristics by Kaushik Kumar,J. Paulo Davim Pdf

Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle. Features: Covers the application of recent and new algorithms Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization Presents the advances of engineering applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering fields Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering

Metaheuristics

El-Ghazali Talbi
Metaheuristics Book PDF

Author : El-Ghazali Talbi
Publisher : John Wiley & Sons
Page : 625 pages
File Size : 41,8 Mb
Release : 2009-05-27
Category : Computers
ISBN : 9780470496909

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Metaheuristics by El-Ghazali Talbi Pdf

A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

Metaheuristics for Finding Multiple Solutions

Mike Preuss,Michael G. Epitropakis,Xiaodong Li,Jonathan E. Fieldsend
Metaheuristics for Finding Multiple Solutions Book PDF

Author : Mike Preuss,Michael G. Epitropakis,Xiaodong Li,Jonathan E. Fieldsend
Publisher : Springer Nature
Page : 322 pages
File Size : 45,9 Mb
Release : 2021-10-22
Category : Computers
ISBN : 9783030795535

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Metaheuristics for Finding Multiple Solutions by Mike Preuss,Michael G. Epitropakis,Xiaodong Li,Jonathan E. Fieldsend Pdf

This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are “multimodal” by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as “niching” methods, because of the nature-inspired “niching” effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc. Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges. To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques. This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

Metaheuristics

Patrick Siarry
Metaheuristics Book PDF

Author : Patrick Siarry
Publisher : Springer
Page : 489 pages
File Size : 53,7 Mb
Release : 2016-12-24
Category : Computers
ISBN : 9783319454030

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Metaheuristics by Patrick Siarry Pdf

Metaheuristics exhibit desirable properties like simplicity, easy parallelizability, and ready applicability to different types of optimization problems. After a comprehensive introduction to the field, the contributed chapters in this book include explanations of the main metaheuristics techniques, including simulated annealing, tabu search, evolutionary algorithms, artificial ants, and particle swarms, followed by chapters that demonstrate their applications to problems such as multiobjective optimization, logistics, vehicle routing, and air traffic management. The authors are leading researchers in this domain, with considerable teaching and applications experience, and the book will be of value to industrial practitioners, graduate students, and research academics.