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Christine Solnon Ant Colony Optimization and Constraint Programming


Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search approaches and metaheuristics, and shows how they can be integrated within constraint programming languages. The second part describes the ant colony optimization metaheuristic and illustrates its capabilities on different constraint satisfaction problems. The third part shows how the ant colony may be integrated within a constraint programming language, thus combining the expressive power of constraint programming languages, to describe problems in a declarative way, and the solving power of ant colony optimization to efficiently solve these problems.

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Patrick Siarry Optimisation in Signal and Image Processing


This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms, and artificial immune systems).

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Alice Yalaoui Optimization of Logistics


This book aims to help engineers, Masters students and young researchers to understand and gain a general knowledge of logistic systems optimization problems and techniques, such as system design, layout, stock management, quality management, lot-sizing or scheduling. It summarizes the evaluation and optimization methods used to solve the most frequent problems. In particular, the authors also emphasize some recent and interesting scientific developments, as well as presenting some industrial applications and some solved instances from real-life cases. Performance evaluation tools (Petri nets, the Markov process, discrete event simulation, etc.) and optimization techniques (branch-and-bound, dynamic programming, genetic algorithms, ant colony optimization, etc.) are presented first. Then, new optimization methods are presented to solve systems design problems, layout problems and buffer-sizing optimization. Forecasting methods, inventory optimization, packing problems, lot-sizing quality management and scheduling are presented with examples in the final chapters.

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Yellow Ant Nest Acrylic Ant Villa Mini Ant Farm Insect Terrarium Ant Colony Breeding Nest

Dan Simon Evolutionary Optimization Algorithms


A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.

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Jenny Valentine Ant Colony

Omid Bozorg-Haddad Meta-heuristic and Evolutionary Algorithms for Engineering Optimization


A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.

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Группа авторов Particle Swarm Optimization


This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies. Since its original development in 1995, PSO has mainly been applied to continuous-discrete heterogeneous strongly non-linear numerical optimization and it is thus used almost everywhere in the world. Its convergence rate also makes it a preferred tool in dynamic optimization.

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Xincheng Zhang LTE Optimization Engineering Handbook


A comprehensive resource containing the operating principles and key insights of LTE networks performance optimization LTE Optimization Engineering Handbook is a comprehensive reference that describes the most current technologies and optimization principles for LTE networks. The text offers an introduction to the basics of LTE architecture, services and technologies and includes details on the key principles and methods of LTE optimization and its parameters. In addition, the author clarifies different optimization aspects such as wireless channel optimization, data optimization, CSFB, VoLTE, and video optimization. With the ubiquitous usage and increased development of mobile networks and smart devices, LTE is the 4G network that will be the only mainstream technology in the current mobile communication system and in the near future. Designed for use by researchers, engineers and operators working in the field of mobile communications and written by a noted engineer and experienced researcher, the LTE Optimization Engineering Handbook provides an essential guide that: Discusses the latest optimization engineering technologies of LTE networks and explores their implementation Features the latest and most industrially relevant applications, such as VoLTE and HetNets Includes a wealth of detailed scenarios and optimization real-world case studies Professionals in the field will find the LTE Optimization Engineering Handbook to be their go-to reference that includes a thorough and complete examination of LTE networks, their operating principles, and the most current information to performance optimization.

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Xin-She Yang Engineering Optimization. An Introduction with Metaheuristic Applications


An accessible introduction to metaheuristics and optimization, featuring powerful and modern algorithms for application across engineering and the sciences From engineering and computer science to economics and management science, optimization is a core component for problem solving. Highlighting the latest developments that have evolved in recent years, Engineering Optimization: An Introduction with Metaheuristic Applications outlines popular metaheuristic algorithms and equips readers with the skills needed to apply these techniques to their own optimization problems. With insightful examples from various fields of study, the author highlights key concepts and techniques for the successful application of commonly-used metaheuristc algorithms, including simulated annealing, particle swarm optimization, harmony search, and genetic algorithms. The author introduces all major metaheuristic algorithms and their applications in optimization through a presentation that is organized into three succinct parts: Foundations of Optimization and Algorithms provides a brief introduction to the underlying nature of optimization and the common approaches to optimization problems, random number generation, the Monte Carlo method, and the Markov chain Monte Carlo method Metaheuristic Algorithms presents common metaheuristic algorithms in detail, including genetic algorithms, simulated annealing, ant algorithms, bee algorithms, particle swarm optimization, firefly algorithms, and harmony search Applications outlines a wide range of applications that use metaheuristic algorithms to solve challenging optimization problems with detailed implementation while also introducing various modifications used for multi-objective optimization Throughout the book, the author presents worked-out examples and real-world applications that illustrate the modern relevance of the topic. A detailed appendix features important and popular algorithms using MATLAB® and Octave software packages, and a related FTP site houses MATLAB code and programs for easy implementation of the discussed techniques. In addition, references to the current literature enable readers to investigate individual algorithms and methods in greater detail. Engineering Optimization: An Introduction with Metaheuristic Applications is an excellent book for courses on optimization and computer simulation at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners working in the fields of mathematics, engineering, computer science, operations research, and management science who use metaheuristic algorithms to solve problems in their everyday work.

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Christine SOLNON - Centre national de la recherche ...

HTML Page of Christine Solnon. I am now member of the CITI lab, and you may find my page here!here!

dblp: Christine Solnon

Madjid Khichane, Patrick Albert, Christine Solnon: Strong Combination of Ant Colony Optimization with Constraint Programming Optimization. CPAIOR 2010: 232-245. 2000 – 2009. see FAQ. What is the meaning of the colors in the publication lists? 2009 [c35] view. electronic edition via DOI; electronic edition @ ieeecomputersociety.org ; unpaywalled version; references & citations . export record ...

Christine Solnon - Google Scholar Citations

This "Cited by" count includes citations to the following articles in Scholar. The ones marked * may be different from the article in the profile.

Download Ant colony optimization and constraint ...

Ant colony optimization and constraint programming by Christine Solnon. 292 Want to read; 35 Currently reading; Published 2010 by Ltd/John Wiley in Hoboken, NJ. Written in English Subjects: Constraint programming (Computer science), Mathematical optimization, Swarm intelligence, Ant algorithms

Christina and Ant Antstead Split

Christina and Ant started dating way back in October 2017, and they tied the knot in a super secret wedding at their home in Newport Beach in December 2018, going with a "winter wonderland" theme...

Christina, Ant Anstead announce split one year after ...

Television personalities Christina Anstead and Ant Anstead are splitting up a year after welcoming their first child together, Christina Anstead announced. In an Instagram post on Friday, the HGTV ...

Ant Colony Optimization for Constraint Satisfaction

Christine Solnon LIRIS, UMR 5205 CNRS / University of Lyon Tutorial at CP’2007. Ant Colony Optimization Application to car sequencing Application to CSPs Conclusion Table of contents 1 Basic principles of Ant Colony Optimization 2 Application to the car sequencing problem 3 Application to binary CSPs 4 Conclusion. Ant Colony Optimization Application to car sequencing Application to CSPs ...

Der wahre Grund, warum Christina und Ant Anstead sich ...

Etwa neun Monate später begrüßten Christina und Ant ihren Sohn Hudson London Anstead. Obwohl die gemischte Familie (sie haben jeweils zwei Kinder aus früheren Ehen) perfekt schien, nahm Christina am 18. September 2020 auf Instagram teil, um zu teilen, dass sie und Ant beschlossen, sich zu trennen. Warum ist die Beziehung also zu Ende gegangen?

Christina & Ant Anstead’s Divorce: A Source Sheds Light on ...

Christina announced their breakup last week, writing on Instagram, “Ant and I have made the difficult decision to separate. We are grateful for each other and as always, our children will remain...

Christina Anstead and Ant Anstead Split After Less Than 2 ...

In a statement posted to her Instagram account on Friday, Christina — who welcomed son Hudson London Anstead with Ant in September 2019 — announced the news of their breakup. "Ant and I have made...

Why Did Christina, Ant Anstead Split? What Went Wrong

Christina and Ant tied the knot in December 2018 during an intimate ceremony at their shared home in Orange County, California. In September 2019, they welcomed their first child together, son...

The real reason Christina and Ant Anstead split

A few months after the exes' divorce got finalized, Christina began dating British television personality Ant Anstead. And just a little over a year later, in December 2018, the two tied the knot...

Ant Colony Optimization and Constraint Programming: Amazon ...

Ant Colony Optimization and Constraint Programming: Amazon.de: Solnon, Christine: Fremdsprachige Bücher

Why Christina Anstead Is "Very Disappointed" Over Ant ...

Christina was already a proud mom to two children, Taylor El Moussa, 10, and Brayden El Moussa, 5, whom she shares with ex-husband Tarek El Moussa. Ant also has two kids, Amelie and Archie, from a...

Christina Anstead felt 'lonely and unhappy' before split ...

Christina is also mom to daughter, Taylor, 10, and son Brayden, 5. She shares the kids with her "Flip or Flop" co-star, ex-husband Tarek El Moussa. Meanwhile, Ant, a native of the United Kingdom,...

Christina Anstead splits from husband Ant Anstead after ...

Christina Anstead and her husband, Ant Anstead, are calling it quits. The "Flip or Flop" star, who is 37, announced the news in an Instagram post Friday. "Ant and I have made the difficult ...

Ant Anstead Revealed What Drove Estranged Wife Christina ...

Before their recent split, Ant Anstead revealed something he did that drove his estranged wife, Christina, "crazy." In an Instagram post on Aug. 2, Anstead shared a video of Christina outside a topical hut over water, and quipped, "I say 'Happy anniversary' to the Wifey EVERY SINGLE SUNDAY!Drives her crazy."

Christina Anstead's Split From Ant Isn't Nasty, Still ...

Christina announced her separation from Ant in an Instagram post Friday, and since then we're told the former couple has been in constant contact because they're co-parenting their 1-year-old son.

Christine Solnon | Laboratoire d'InfoRmatique en Image et ...

Christine Solnon (2010). "Ant Colony Optimization and Constraint Programming". John Wiley & Sons, Inc.. HAL : hal-01483570. 2009 (9) Conferences (8) International conferences with peer review (8) Marc Mouret, Christine Solnon & Christian Wolf (2009). "Classification of images based on Hidden Markov Models".

Christine SOLNON : New optimisation tools for smart and sustainable cities

Christine SOLNON Deputy president of the TUBA (Le Tube a experimentations urbaines), LabEx IMU, Lyon, France A first key point is to design efficient tools that scale well on real data. A second ...

9781848211308: Ant Colony Optimization and Constraint ...

Solnon, Christine. 3.5 avg rating • (2 ratings by Goodreads) Hardcover ISBN 10: 1848211309 ISBN 13: 9781848211308. Publisher: Wiley-ISTE, 2010. This specific ISBN edition is currently not available. View all copies of this ISBN edition: Synopsis; About this title; Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization ...

Christina and Ant Anstead's friends are 'shocked' at their ...

Christina and Ant Anstead announced their separation on Friday, but the couple kept the news so quiet that their friends were shocked by their Instagram post.

Christina El Moussa And Ant Anstead Had 'Conflicts' After ...

It seems like Christina El Moussa was not in the honeymoon phase anymore with her husband, Ant Anstead.In fact, the two — who announced their split on Friday, September 18, after less than two ...

Christina El Moussa and Ant Anstead announce separation

Christina and Ant married in December 2018 at their Newport Beach, Calif. home. They began dating in October 2017. Filed under celebrity divorces, christina el moussa, hgtv, 9/22/20. Share this ...

Christine Solnon - amazon.com

Follow Christine Solnon and explore their bibliography from Amazon.com's Christine Solnon Author Page.

Christina and Ant Anstead Reportedly 'Grew Apart' Ahead of ...

Fans were shocked to hear that Christina Anstead and Ant Anstead had split after almost two years of marriage.The pair, who also have children from previous relationships, share 1-year-old son Hudson. While this news was shocking to many, a report from Life & Style purports the two had been growing apart for some time.. A source told Life & Style that "no one saw this coming," about their split.

How Christina and Ant Anstead Are Coping Since Separating

On Friday, Christina Anstead shared the news that she would be separating from husband Ant Anstead after less than two years of marriage. "We are grateful for each other and as always, our ...

Christine SOLNON | Institut National des Sciences ...

Christine SOLNON of Institut National des Sciences Appliquées de Lyon, Lyon (INSA Lyon) | Read 90 publications | Contact Christine SOLNON

Christina Anstead’s 1st Pics Since Split From Husband Ant ...

Christina Anstead had a somber looking expression on her face during her first outing since announcing her split from husband Ant on Sep. 18. Christina Anstead looked serious and somewhat sad as ...

Ant colony optimization and constraint programming (Book ...

Get this from a library! Ant colony optimization and constraint programming. [Christine Solnon] -- Ant colony optimization is a metaheuristic - or very generally a form of "black-box" problem-solving algorithm-which has been successfully applied to a wide range of combinatorial optimization ...

Ant Colony Optimization for Multi-Objective Optimization ...

DOI: 10.1109/ICTAI.2007.108 Corpus ID: 9337904. Ant Colony Optimization for Multi-Objective Optimization Problems @article{Alaya2007AntCO, title={Ant Colony Optimization for Multi-Objective Optimization Problems}, author={In{\`e}s Alaya and Christine Solnon and Khaled Gh{\'e}dira}, journal={19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007)}, year={2007 ...

[PDF] Ant Colony Optimization and Constraint Programming ...

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which ...

Электронная книга: Christine Solnon. Ant Colony ...

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which ...

Ant Colony Optimization and Constraint Programming | Wiley ...

The third part shows how the ant colony may be integrated within a constraint programming language, thus combining the expressive power of constraint programming languages, to describe problems in a declarative way, and the solving power of ant colony optimization to efficiently solve these problems. Reviews "In this volume, Solnon (U. of Lyon, France) introduces ant colony optimization and ...

Christina Anstead Felt ‘Lonely and Unhappy’ Before Divorce ...

Christina and Ant Anstead were having trouble navigating life with their blended families before she announced their split, a source tells PEOPLE. The Christina on the Coast star, 37, revealed ...

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Ant Colony Optimization and Constraint Programming ...

Ant Colony Optimization and Constraint Programming: Christine Solnon: 9781848211308: Books - Amazon.ca

A reactive framework for Ant Colony Optimization

christine.solnon@liris.cnrs.fr Abstract. We introduce two reactive frameworks for dynamic adapat-ing some parameters of an Ant Colony Optimization (ACO) algorithm. Both reactive frameworks use ACO ...

Christina and Ant Anstead’s Friends Are ‘Shocked’ By Split

The Christina on the Coast star, 37, announced via Instagram on Friday, September 18, that she and Ant, 41, are separating after less than two years of marriage. Christina Anstead and Ant Anstead ...

Christina, Ant Anstead Split After Less Than 2 Years of ...

Ant Anstead and Christina Anstead AFF-USA/Shutterstock. The couple tied the knot in December 2018 and welcomed their son, Hudson, in September 2019. Christina was previously married to Tarek El ...

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Ant Colony Optimization and Constraint Programming

Ant Colony Optimization and Constraint Programming by Christine Solnon. Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into ...

Ant colony optimization and constraint programming (eBook ...

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Christine Solnon: free download. Ebooks library. On-line ...

Christine Solnon: free download. Ebooks library. On-line books store on Z-Library | B–OK. Download books for free. Find books. 5,346,373 books books; 77,518,212 articles articles; ZLibrary Home; Home; Toggle navigation. Sign in . Login; Registration; Fundraising: 44.7% raised; Books; Add book; Categories; Most Popular; Recently Added; Z-Library Project ; Top Z-Librarians; Blog; Part of Z ...

Why Did Christina Anstead Leave Ant? Their Split Was a ...

In October 2017, Christina and Ant met through mutual friends and started publicly dating. The relationship came a few months before Christina’s divorce from ex-husband Tarek El Moussa was finalized and, at the time, it seemed like Christina was about to get her do-over. Unfortunately, that wasn't the case and now, people are wondering what happened. Source: Instagram. Why did Christina ...

A Comparative Study of Ant Colony Optimization and ...

Christine Solnon; Khaled Ghédira; Conference paper. 8 Citations; 856 Downloads; Part of the Lecture Notes in Computer Science book series (LNCS, volume 3906) Abstract. Many applications involve matching two graphs in order to identify their common features and compute their similarity. In this paper, we address the problem of computing a graph similarity measure based on a multivalent graph ...

Ant Algorithm for the Graph Matching Problem | SpringerLink

Christine Solnon; Khaled Ghédira; Conference paper. 10 Citations; 561 Downloads; Part of the Lecture Notes in Computer Science book series (LNCS, volume 3448) Abstract. This paper describes a new Ant Colony Optimization (ACO) algorithm for solving Graph Matching Problems, the goal of which is to find the best matching between vertices of multi-labeled graphs. This new ACO algorithm is ...

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Christiane Ant. Dipl. Sozial-Pädagogin (FH) Kinder- und Jugendlichenpsychotherapeutin. Praxis für Kinder- und Jugendpsychotherapie. KJP C. Ant Christiane Ant Kirchstr. 52 52499 Baesweiler. Telefon 02401 / 69 21 465. Dies ist keine Notfallpraxis. In akuten Krisensituationen melden Sie sich bitte an den ärztlichen Notdienst oder das Uniklinikum Aachen (Tel: 0241-800). Die Psychotherapeutische ...

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Группа авторов Metaheuristics


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.

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Enrique Alba Parallel Metaheuristics


Solving complex optimization problems with parallel metaheuristics Parallel Metaheuristics brings together an international group of experts in parallelism and metaheuristics to provide a much-needed synthesis of these two fields. Readers discover how metaheuristic techniques can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields of telecommunications and bioinformatics. This volume fills a long-existing gap, allowing researchers and practitioners to develop efficient metaheuristic algorithms to find solutions. The book is divided into three parts: * Part One: Introduction to Metaheuristics and Parallelism, including an Introduction to Metaheuristic Techniques, Measuring the Performance of Parallel Metaheuristics, New Technologies in Parallelism, and a head-to-head discussion on Metaheuristics and Parallelism * Part Two: Parallel Metaheuristic Models, including Parallel Genetic Algorithms, Parallel Genetic Programming, Parallel Evolution Strategies, Parallel Ant Colony Algorithms, Parallel Estimation of Distribution Algorithms, Parallel Scatter Search, Parallel Variable Neighborhood Search, Parallel Simulated Annealing, Parallel Tabu Search, Parallel GRASP, Parallel Hybrid Metaheuristics, Parallel Multi-Objective Optimization, and Parallel Heterogeneous Metaheuristics * Part Three: Theory and Applications, including Theory of Parallel Genetic Algorithms, Parallel Metaheuristics Applications, Parallel Metaheuristics in Telecommunications, and a final chapter on Bioinformatics and Parallel Metaheuristics Each self-contained chapter begins with clear overviews and introductions that bring the reader up to speed, describes basic techniques, and ends with a reference list for further study. Packed with numerous tables and figures to illustrate the complex theory and processes, this comprehensive volume also includes numerous practical real-world optimization problems and their solutions. This is essential reading for students and researchers in computer science, mathematics, and engineering who deal with parallelism, metaheuristics, and optimization in general.

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Singiresu S. Rao Engineering Optimization


The revised and updated new edition of the popular optimization book for engineers The thoroughly revised and updated fifth edition of Engineering Optimization: Theory and Practice offers engineers a guide to the important optimization methods that are commonly used in a wide range of industries. The author—a noted expert on the topic—presents both the classical and most recent optimizations approaches. The book introduces the basic methods and includes information on more advanced principles and applications. The fifth edition presents four new chapters: Solution of Optimization Problems Using MATLAB; Metaheuristic Optimization Methods; Multi-Objective Optimization Methods; and Practical Implementation of Optimization. All of the book's topics are designed to be self-contained units with the concepts described in detail with derivations presented. The author puts the emphasis on computational aspects of optimization and includes design examples and problems representing different areas of engineering. Comprehensive in scope, the book contains solved examples, review questions and problems, and is accompanied by a website hosting a solutions manual. This important book: Offers an updated edition of the classic work on optimization Includes approaches that are appropriate for all branches of engineering Contains numerous practical design and engineering examples Offers more than 140 illustrative examples, 500 plus references in the literature of engineering optimization, and more than 500 review questions and answers Demonstrates the use of MATLAB for solving different types of optimization problems using different techniques Written for students across all engineering disciplines, the revised edition of Engineering Optimization: Theory and Practice is the comprehensive book that covers the new and recent methods of optimization and reviews the principles and applications.

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Xin-She Yang Optimization Techniques and Applications with Examples


A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.

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John Nash C. Nonlinear Parameter Optimization Using R Tools


Nonlinear Parameter Optimization Using R John C. Nash, Telfer School of Management, University of Ottawa, Canada A systematic and comprehensive treatment of optimization software using R In recent decades, optimization techniques have been streamlined by computational and artificial intelligence methods to analyze more variables, especially under non–linear, multivariable conditions, more quickly than ever before. Optimization is an important tool for decision science and for the analysis of physical systems used in engineering. Nonlinear Parameter Optimization with R explores the principal tools available in R for function minimization, optimization, and nonlinear parameter determination and features numerous examples throughout. Nonlinear Parameter Optimization with R: Provides a comprehensive treatment of optimization techniques Examines optimization problems that arise in statistics and how to solve them using R Enables researchers and practitioners to solve parameter determination problems Presents traditional methods as well as recent developments in R Is supported by an accompanying website featuring R code, examples and datasets Researchers and practitioners who have to solve parameter determination problems who are users of R but are novices in the field optimization or function minimization will benefit from this book. It will also be useful for scientists building and estimating nonlinear models in various fields such as hydrology, sports forecasting, ecology, chemical engineering, pharmaco-kinetics, agriculture, economics and statistics.

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Vangelis Th. Paschos Applications of Combinatorial Optimization


Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aims to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. “Applications of Combinatorial Optimization” is presenting a certain number among the most common and well-known applications of Combinatorial Optimization.

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Kwang-Yong Kim Design Optimization of Fluid Machinery. Applying Computational Fluid Dynamics and Numerical Optimization


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