Memetic Computation

Download Memetic Computation PDF Online Free

Author :
Release : 2018-12-18
Genre : Technology & Engineering
Kind :
Book Rating : 295/5 ( reviews)

Memetic Computation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Memetic Computation write by Abhishek Gupta. This book was released on 2018-12-18. Memetic Computation available in PDF, EPUB and Kindle. This book bridges the widening gap between two crucial constituents of computational intelligence: the rapidly advancing technologies of machine learning in the digital information age, and the relatively slow-moving field of general-purpose search and optimization algorithms. With this in mind, the book serves to offer a data-driven view of optimization, through the framework of memetic computation (MC). The authors provide a summary of the complete timeline of research activities in MC – beginning with the initiation of memes as local search heuristics hybridized with evolutionary algorithms, to their modern interpretation as computationally encoded building blocks of problem-solving knowledge that can be learned from one task and adaptively transmitted to another. In the light of recent research advances, the authors emphasize the further development of MC as a simultaneous problem learning and optimization paradigm with the potential to showcase human-like problem-solving prowess; that is, by equipping optimization engines to acquire increasing levels of intelligence over time through embedded memes learned independently or via interactions. In other words, the adaptive utilization of available knowledge memes makes it possible for optimization engines to tailor custom search behaviors on the fly – thereby paving the way to general-purpose problem-solving ability (or artificial general intelligence). In this regard, the book explores some of the latest concepts from the optimization literature, including, the sequential transfer of knowledge across problems, multitasking, and large-scale (high dimensional) search, systematically discussing associated algorithmic developments that align with the general theme of memetics. The presented ideas are intended to be accessible to a wide audience of scientific researchers, engineers, students, and optimization practitioners who are familiar with the commonly used terminologies of evolutionary computation. A full appreciation of the mathematical formalizations and algorithmic contributions requires an elementary background in probability, statistics, and the concepts of machine learning. A prior knowledge of surrogate-assisted/Bayesian optimization techniques is useful, but not essential.

Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling

Download Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling PDF Online Free

Author :
Release : 2021-11-13
Genre : Technology & Engineering
Kind :
Book Rating : 159/5 ( reviews)

Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling write by Kyle Robert Harrison. This book was released on 2021-11-13. Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling available in PDF, EPUB and Kindle. This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times. It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.

Handbook of Memetic Algorithms

Download Handbook of Memetic Algorithms PDF Online Free

Author :
Release : 2011-10-18
Genre : Mathematics
Kind :
Book Rating : 469/5 ( reviews)

Handbook of Memetic Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Memetic Algorithms write by Ferrante Neri. This book was released on 2011-10-18. Handbook of Memetic Algorithms available in PDF, EPUB and Kindle. Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes. “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now. A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem, memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, a great attention has been given by the editors to make it a compact and smooth work which covers all the main areas of computational intelligence optimization. It is not only a necessary read for researchers working in the research area, but also a useful handbook for practitioners and engineers who need to address real-world optimization problems. In addition, the book structure makes it an interesting work also for graduate students and researchers is related fields of mathematics and computer science.

Swarm, Evolutionary, and Memetic Computing

Download Swarm, Evolutionary, and Memetic Computing PDF Online Free

Author :
Release : 2011-12-15
Genre : Computers
Kind :
Book Rating : 723/5 ( reviews)

Swarm, Evolutionary, and Memetic Computing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Swarm, Evolutionary, and Memetic Computing write by Bijaya Ketan Panigrahi. This book was released on 2011-12-15. Swarm, Evolutionary, and Memetic Computing available in PDF, EPUB and Kindle. These two volumes, LNCS 7076 and LNCS 7077, constitute the refereed proceedings of the Second International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011, held in Visakhapatnam, India, in December 2011. The 124 revised full papers presented in both volumes were carefully reviewed and selected from 422 submissions. The papers explore new application areas, feature new bio-inspired algorithms for solving specific hard optimization problems, and review the latest progresses in the cutting-edge research with swarm, evolutionary, and memetic computing in both theoretical and practical aspects.

Recent Advances in Memetic Algorithms

Download Recent Advances in Memetic Algorithms PDF Online Free

Author :
Release : 2006-06-22
Genre : Mathematics
Kind :
Book Rating : 635/5 ( reviews)

Recent Advances in Memetic Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recent Advances in Memetic Algorithms write by William E. Hart. This book was released on 2006-06-22. Recent Advances in Memetic Algorithms available in PDF, EPUB and Kindle. Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. This monograph presents a rich state-of-the-art gallery of works on memetic algorithms. Recent Advances in Memetic Algorithms is the first book that focuses on this technology as the central topical matter. This book gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to memetic algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.