Heuristics and Hyper-Heuristics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Heuristics and Hyper-Heuristics PDF full book. Access full book title Heuristics and Hyper-Heuristics by Javier Del Ser Lorente. Download full books in PDF and EPUB format.
Author: Javier Del Ser Lorente
Publisher: BoD – Books on Demand
ISBN: 9535133837
Category : Computers
Languages : en
Pages : 137
Get Book Here
Book Description
In the last few years, the society is witnessing ever-growing levels of complexity in the optimization paradigms lying at the core of different applications and processes. This augmented complexity has motivated the adoption of heuristic methods as a means to balance the Pareto trade-off between computational efficiency and the quality of the produced solutions to the problem at hand. The momentum gained by heuristics in practical applications spans further towards hyper-heuristics, which allow constructing ensembles of simple heuristics to handle efficiently several problems of a single class. In this context, this short book compiles selected applications of heuristics and hyper-heuristics for combinatorial optimization problems, including scheduling and other assorted application scenarios.
Author: Javier Del Ser Lorente
Publisher: BoD – Books on Demand
ISBN: 9535133837
Category : Computers
Languages : en
Pages : 137
Get Book Here
Book Description
In the last few years, the society is witnessing ever-growing levels of complexity in the optimization paradigms lying at the core of different applications and processes. This augmented complexity has motivated the adoption of heuristic methods as a means to balance the Pareto trade-off between computational efficiency and the quality of the produced solutions to the problem at hand. The momentum gained by heuristics in practical applications spans further towards hyper-heuristics, which allow constructing ensembles of simple heuristics to handle efficiently several problems of a single class. In this context, this short book compiles selected applications of heuristics and hyper-heuristics for combinatorial optimization problems, including scheduling and other assorted application scenarios.
Author: Nelishia Pillay
Publisher: Springer
ISBN: 331996514X
Category : Computers
Languages : en
Pages : 134
Get Book Here
Book Description
This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, provides an overview of selection constructive, selection perturbative, generation constructive and generation perturbative hyper-heuristics, and then a formal definition of hyper-heuristics. The chapters in the second part of the book examine applications of hyper-heuristics in vehicle routing, nurse rostering, packing and examination timetabling. The third part of the book presents advanced topics and then a summary of the field and future research directions. Finally the appendices offer details of the HyFlex framework and the EvoHyp toolkit, and then the definition, problem model and constraints for the most tested combinatorial optimization problems. The book will be of value to graduate students, researchers, and practitioners.
Author: Gerd Gigerenzer
Publisher: MIT Press
ISBN: 0262072750
Category : Law
Languages : en
Pages : 502
Get Book Here
Book Description
Experts in law, psychology, and economics explore the power of "fast and frugal" heuristics in the creation and implementation of law In recent decades, the economists' concept of rational choice has dominated legal reasoning. And yet, in practical terms, neither the lawbreakers the law addresses nor officers of the law behave as the hyperrational beings postulated by rational choice. Critics of rational choice and believers in "fast and frugal heuristics" propose another approach: using certain formulations or general principles (heuristics) to help navigate in an environment that is not a well-ordered setting with an occasional disturbance, as described in the language of rational choice, but instead is fundamentally uncertain or characterized by an unmanageable degree of complexity. This is the intuition behind behavioral law and economics. In Heuristics and the Law, experts in law, psychology, and economics explore the conceptual and practical power of the heuristics approach in law. They discuss legal theory; modeling and predicting the problems the law purports to solve; the process of making law, in the legislature or in the courtroom; the application of existing law in the courts, particularly regarding the law of evidence; and implementation of the law and the impact of law on behavior. Contributors Ronald J. Allen, Hal R. Arkes, Peter Ayton, Susanne Baer, Martin Beckenkamp, Robert Cooter, Leda Cosmides, Mandeep K. Dhami, Robert C. Ellickson, Christoph Engel, Richard A. Epstein, Wolfgang Fikentscher, Axel Flessner, Robert H. Frank, Bruno S. Frey, Gerd Gigerenzer, Paul W. Glimcher, Daniel G. Goldstein, Chris Guthrie, Jonathan Haidt, Reid Hastie, Ralph Hertwig, Eric J. Johnson, Jonathan J. Koehler, Russell Korobkin, Stephanie Kurzenhäuser, Douglas A. Kysar, Donald C. Langevoort, Richard Lempert, Stefan Magen, Callia Piperides, Jeffrey J. Rachlinski, Clara Sattler de Sousa e Brito, Joachim Schulz, Victoria A. Shaffer, Indra Spiecker genannt Döhmann, John Tooby, Gerhard Wagner, Elke U. Weber, Bernd Wittenbrink
Author: Lv, Zhihan
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 332
Get Book Here
Book Description
The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.
Author: Carlos Cotta
Publisher: Springer Science & Business Media
ISBN: 3540794379
Category : Computers
Languages : en
Pages : 276
Get Book Here
Book Description
This cutting edge volume presents recent advances in the area of adaptativeness in metaheuristic optimization. It includes up-to-date reviews of hyperheuristics and self-adaptation in evolutionary algorithms.
Author: Rafael Martí
Publisher: Springer
ISBN: 9783319071237
Category : Computers
Languages : en
Pages : 3000
Get Book Here
Book Description
Heuristics are strategies using readily accessible, loosely applicable information to control problem solving. Algorithms, for example, are a type of heuristic. By contrast, Metaheuristics are methods used to design Heuristics and may coordinate the usage of several Heuristics toward the formulation of a single method. GRASP (Greedy Randomized Adaptive Search Procedures) is an example of a Metaheuristic. To the layman, heuristics may be thought of as ‘rules of thumb’ but despite its imprecision, heuristics is a very rich field that refers to experience-based techniques for problem-solving, learning, and discovery. Any given solution/heuristic is not guaranteed to be optimal but heuristic methodologies are used to speed up the process of finding satisfactory solutions where optimal solutions are impractical. The introduction to this Handbook provides an overview of the history of Heuristics along with main issues regarding the methodologies covered. This is followed by Chapters containing various examples of local searches, search strategies and Metaheuristics, leading to an analyses of Heuristics and search algorithms. The reference concludes with numerous illustrations of the highly applicable nature and implementation of Heuristics in our daily life. Each chapter of this work includes an abstract/introduction with a short description of the methodology. Key words are also necessary as part of top-matter to each chapter to enable maximum search engine optimization. Next, chapters will include discussion of the adaptation of this methodology to solve a difficult optimization problem, and experiments on a set of representative problems.
Author: Changhe Li
Publisher: Springer Nature
ISBN: 9819732867
Category :
Languages : en
Pages : 369
Get Book Here
Book Description
Author: Toshihide Ibaraki
Publisher: Springer Science & Business Media
ISBN: 0387253831
Category : Mathematics
Languages : en
Pages : 419
Get Book Here
Book Description
Metaheuristics: Progress as Real Problem Solvers is a peer-reviewed volume of eighteen current, cutting-edge papers by leading researchers in the field. Included are an invited paper by F. Glover and G. Kochenberger, which discusses the concept of Metaheuristic agent processes, and a tutorial paper by M.G.C. Resende and C.C. Ribeiro discussing GRASP with path-relinking. Other papers discuss problem-solving approaches to timetabling, automated planograms, elevators, space allocation, shift design, cutting stock, flexible shop scheduling, colorectal cancer and cartography. A final group of methodology papers clarify various aspects of Metaheuristics from the computational view point.
Author: Pascal van Hentenryck
Publisher: Springer Science & Business Media
ISBN: 144191644X
Category : Mathematics
Languages : en
Pages : 562
Get Book Here
Book Description
Hybrid Optimization focuses on the application of artificial intelligence and operations research techniques to constraint programming for solving combinatorial optimization problems. This book covers the most relevant topics investigated in the last ten years by leading experts in the field, and speculates about future directions for research. This book includes contributions by experts from different but related areas of research including constraint programming, decision theory, operations research, SAT, artificial intelligence, as well as others. These diverse perspectives are actively combined and contrasted in order to evaluate their relative advantages. This volume presents techniques for hybrid modeling, integrated solving strategies including global constraints, decomposition techniques, use of relaxations, and search strategies including tree search local search and metaheuristics. Various applications of the techniques presented as well as supplementary computational tools are also discussed.
Author: Mansour Eddaly
Publisher: Springer Nature
ISBN: 9811938881
Category : Computers
Languages : en
Pages : 231
Get Book Here
Book Description
Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.
