Recent Advances On Meta Heuristics And Their Application To Real Scenarios


Recent Advances On Meta Heuristics And Their Application To Real Scenarios
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Recent Advances On Meta Heuristics And Their Application To Real Scenarios


Recent Advances On Meta Heuristics And Their Application To Real Scenarios
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Author : Javier Del Ser Lorente
language : en
Publisher: BoD – Books on Demand
Release Date : 2013-01-30

Recent Advances On Meta Heuristics And Their Application To Real Scenarios written by Javier Del Ser Lorente and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-30 with Computers categories.


This book aims at attracting the interest of researchers and practitioners around the applicability of meta-heuristic algorithms to practical scenarios arising from different knowledge disciplines. Emphasis is placed on evolutionary algorithms and swarm intelligence as computational means to efficiently balance the tradeoff between optimality of the produced solutions and the complexity derived from their estimation. In summary, this book serves as a good start point for early-stage investigators in the initial steps of their research on meta-heuristics, grounded on both a thorough literature review and the practical orientation of its contents.



Meta Heuristic Techniques In Software Engineering And Its Applications


Meta Heuristic Techniques In Software Engineering And Its Applications
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Author : Mihir Narayan Mohanty
language : en
Publisher: Springer Nature
Release Date : 2022-10-17

Meta Heuristic Techniques In Software Engineering And Its Applications written by Mihir Narayan Mohanty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-17 with Technology & Engineering categories.


This book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques, along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains, are discussed in this book and help global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. Novel ways are also discovered to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms leads beginners to apply current approaches to optimization problems. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract researchers and practitioners to apply hybrid metaheuristics in real scenarios.



Meta Heuristic Algorithms In Production Engineering


Meta Heuristic Algorithms In Production Engineering
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Author : Aidin Delgoshaei
language : en
Publisher: Academic Press
Release Date : 2022-02-01

Meta Heuristic Algorithms In Production Engineering written by Aidin Delgoshaei and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-01 with Business & Economics categories.


Meta-Heuristic Algorithms in Production Engineering is a ground-breaking exploration of the new ways that meta-heuristic algorithms can be used to optimize planning and scheduling problems in production engineering. Putting equal emphasis on mathematics and engineering knowledge, this book provides the perfect guide to using meta-heuristics in a range of innovative ways, addressing problems in areas like facility location, location-allocation, job shop-scheduling, flow shop-scheduling, and group technology. To start with, the author draws on production engineering knowledge to help the reader to analyse and frame their problem for solution. Next, the different algorithms are dealt with in detail, starting with the meta-heuristic, its logic, and its standard mechanism. Then the very latest applications are described, before fully worked examples are provided with MATLAB code. This invaluable resource also acts as a review of the latest advances in meta-heuristics including genetic algorithm, simulated annealing, tabu search, ant colony optimization, particle swarm methods, and artificial neural networks. Provides step-by-step instructions to applying meta-heuristics algorithms to real production engineering problems Explores numerous pioneering applications of meta-heuristics in industrial engineering and industrial management Examines a wide range of algorithms, enabling comparison and informing selection decisions · Includes Matlab codes that will save users many hours of their own time and effort



Metaheuristics For Finding Multiple Solutions


Metaheuristics For Finding Multiple Solutions
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Author : Mike Preuss
language : en
Publisher: Springer Nature
Release Date : 2021-10-22

Metaheuristics For Finding Multiple Solutions written by Mike Preuss and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.


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.



Recent Developments In Metaheuristics


Recent Developments In Metaheuristics
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Author : Lionel Amodeo
language : en
Publisher: Springer
Release Date : 2017-09-18

Recent Developments In Metaheuristics written by Lionel Amodeo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-18 with Business & Economics categories.


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.



Swarm Intelligence Based Optimization


Swarm Intelligence Based Optimization
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Author : Patrick Siarry
language : en
Publisher: Springer
Release Date : 2014-11-27

Swarm Intelligence Based Optimization written by Patrick Siarry and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-27 with Computers categories.


This book constitutes the thoroughly refereed post-conference proceedings of the 1st International Conference on Swarm Intelligence Based Optimization, ICSIBO 2014, held in Mulhouse, France, in May 2014. The 20 full papers presented were carefully reviewed and selected from 48 submissions. Topics of interest presented and discussed in the conference focuses on the theoretical progress of swarm intelligence metaheuristics and their applications in areas such as: theoretical advances of swarm intelligence metaheuristics, combinatorial, discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large-scale optimization, artificial immune systems, particle swarms, ant colony, bacterial foraging, artificial bees, fireflies algorithm, hybridization of algorithms, parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles, adaptation and applications of swarm intelligence principles to real world problems in various domains.



Meta Heuristics


Meta Heuristics
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Author : Stefan Voß
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Meta Heuristics written by Stefan Voß and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.


Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.



Essays And Surveys In Metaheuristics


Essays And Surveys In Metaheuristics
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Author : Celso C. Ribeiro
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Essays And Surveys In Metaheuristics written by Celso C. Ribeiro and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


Finding exact solutions to many combinatorial optimization problems in busi ness, engineering, and science still poses a real challenge, despite the impact of recent advances in mathematical programming and computer technology. New fields of applications, such as computational biology, electronic commerce, and supply chain management, bring new challenges and needs for algorithms and optimization techniques. Metaheuristics are master procedures that guide and modify the operations of subordinate heuristics, to produce improved approx imate solutions to hard optimization problems with respect to more simple algorithms. They also provide fast and robust tools, producing high-quality solutions in reasonable computation times. The field of metaheuristics has been fast evolving in recent years. Tech niques such as simulated annealing, tabu search, genetic algorithms, scatter search, greedy randomized adaptive search, variable neighborhood search, ant systems, and their hybrids are currently among the most efficient and robust optimization strategies to find high-quality solutions to many real-life optimiza tion problems. A very large nmnber of successful applications of metaheuristics are reported in the literature and spread throughout many books, journals, and conference proceedings. A series of international conferences entirely devoted to the theory, applications, and computational developments in metaheuristics has been attracting an increasing number of participants, from universities and the industry.



Recent Advances In Hybrid Metaheuristics For Data Clustering


Recent Advances In Hybrid Metaheuristics For Data Clustering
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Author : Sourav De
language : en
Publisher: John Wiley & Sons
Release Date : 2020-06-02

Recent Advances In Hybrid Metaheuristics For Data Clustering written by Sourav De 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 2020-06-02 with Computers categories.


An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics and their application to data clustering. Metaheuristics are designed to tackle complex clustering problems where classical clustering algorithms have failed to be either effective or efficient. The authors—noted experts on the topic—provide a text that can aid in the design and development of hybrid metaheuristics to be applied to data clustering. The book includes performance analysis of the hybrid metaheuristics in relationship to their conventional counterparts. In addition to providing a review of data clustering, the authors include in-depth analysis of different optimization algorithms. The text offers a step-by-step guide in the build-up of hybrid metaheuristics and to enhance comprehension. In addition, the book contains a range of real-life case studies and their applications. This important text: Includes performance analysis of the hybrid metaheuristics as related to their conventional counterparts Offers an in-depth analysis of a range of optimization algorithms Highlights a review of data clustering Contains a detailed overview of different standard metaheuristics in current use Presents a step-by-step guide to the build-up of hybrid metaheuristics Offers real-life case studies and applications Written for researchers, students and academics in computer science, mathematics, and engineering, Recent Advances in Hybrid Metaheuristics for Data Clustering provides a text that explores the current data clustering approaches using a range of computational intelligence techniques.



Advances In Metaheuristics For Hard Optimization


Advances In Metaheuristics For Hard Optimization
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Author : Patrick Siarry
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-06

Advances In Metaheuristics For Hard Optimization written by Patrick Siarry and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-06 with Mathematics categories.


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.