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Cultural Algorithms [electronic resource] : Recent Advances /

By: Contributor(s): Material type: TextTextSeries: Engineering Optimization: Methods and ApplicationsPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2022Edition: 1st ed. 2022Description: XIII, 271 p. 76 illus., 35 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789811946332
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q342
Online resources:
Contents:
Introduction to Culture -- Introduction to optimization -- Cultural Algorithms (CAs) -- Applications of Engineering. .
In: Springer Nature eBookSummary: This book covers the latest advances in Cultural Algorithms, their general framework, different variants, hybridized versions with other meta-heuristic and search techniques, and their applications. Cultural Algorithms are meta-heuristic numerical optimization techniques inspired by the bio-cultural evolutionary theory, in which both types of vertical and horizontal learning behaviors are modeled. The book includes well-briefed basics of optimization and theoretical backgrounds of Cultural Algorithms in its initial chapters and then discusses their applications in different branches of science and engineering. It provides detailed mathematical formulations and algorithmic pseudo-codes of hybridized, extended, and multi-population variants of cultural algorithms. The book will serve the research students, fellows, professors, and industry professionals to implement real-time applications of Cultural Algorithms.
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Introduction to Culture -- Introduction to optimization -- Cultural Algorithms (CAs) -- Applications of Engineering. .

This book covers the latest advances in Cultural Algorithms, their general framework, different variants, hybridized versions with other meta-heuristic and search techniques, and their applications. Cultural Algorithms are meta-heuristic numerical optimization techniques inspired by the bio-cultural evolutionary theory, in which both types of vertical and horizontal learning behaviors are modeled. The book includes well-briefed basics of optimization and theoretical backgrounds of Cultural Algorithms in its initial chapters and then discusses their applications in different branches of science and engineering. It provides detailed mathematical formulations and algorithmic pseudo-codes of hybridized, extended, and multi-population variants of cultural algorithms. The book will serve the research students, fellows, professors, and industry professionals to implement real-time applications of Cultural Algorithms.

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