Handbook of Metaheuristic Algorithms

This book PDF is perfect for those who love Computers genre, written by Chun-Wei Tsai and published by Elsevier which was released on 30 May 2023 with total hardcover pages 624. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Handbook of Metaheuristic Algorithms books below.

Handbook of Metaheuristic Algorithms
Handbook of Metaheuristic Algorithms
Author : Chun-Wei Tsai
File Size : 54,9 Mb
Publisher : Elsevier
Language : English
Release Date : 30 May 2023
ISBN : 9780443191091
Pages : 624 pages
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Handbook of Metaheuristic Algorithms by Chun-Wei Tsai Book PDF Summary

Handbook of Metaheuristic Algorithms: From Fundamental Theories to Advanced Applications provides a brief introduction to metaheuristic algorithms from the ground up, including basic ideas and advanced solutions. Although readers may be able to find source code for some metaheuristic algorithms on the Internet, the coding styles and explanations are generally quite different, and thus requiring expanded knowledge between theory and implementation. This book can also help students and researchers construct an integrated perspective of metaheuristic and unsupervised algorithms for artificial intelligence research in computer science and applied engineering domains. Metaheuristic algorithms can be considered the epitome of unsupervised learning algorithms for the optimization of engineering and artificial intelligence problems, including simulated annealing (SA), tabu search (TS), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), differential evolution (DE), and others. Distinct from most supervised learning algorithms that need labeled data to learn and construct determination models, metaheuristic algorithms inherit characteristics of unsupervised learning algorithms used for solving complex engineering optimization problems without labeled data, just like self-learning, to find solutions to complex problems. Presents a unified framework for metaheuristics and describes well-known algorithms and their variants Introduces fundamentals and advanced topics for solving engineering optimization problems, e.g., scheduling problems, sensors deployment problems, and clustering problems Includes source code based on the unified framework for metaheuristics used as examples to show how TS, SA, GA, ACO, PSO, DE, parallel metaheuristic algorithm, hybrid metaheuristic, local search, and other advanced technologies are realized in programming languages such as C++ and Python

Handbook of Metaheuristic Algorithms

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Handbook of Metaheuristic Algorithms: From Fundamental Theories to Advanced Applications provides a brief introduction to metaheuristic algorithms from the ground up, including basic ideas and advanced solutions. Although readers may be able to find source code for some metaheuristic algorithms on the Internet, the coding styles and explanations are generally

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