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Computational Intelligence-based Optimization Algorithms

Babak Zolghadr-Asli
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A01=Babak Zolghadr-Asli
algorithms
Ant Colony Optimization Algorithm
artificial intelligence techniques
Author_Babak Zolghadr-Asli
Biogeography Based Optimization Algorithm
Category=PBW
Category=UMB
Category=UYA
combinatorial optimisation
Computational intelligence-based optimization methods
Computational Standpoint
Cuckoo Search Algorithm
Decision Variables
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Firefly Algorithm
Genetic Algorithm
global search strategies
Gravitational Search Algorithm
Greedy Strategy
Invasive Weed Optimization Algorithm
Local Search
mathematical programming
Meta-heuristic Algorithm
Meta-heuristic Optimization
Meta-heuristic Optimization Algorithm
meta-heuristic optimization algorithms
metaheuristic algorithms
Non-improving Moves
optimisation algorithm code examples
Parallelized Computation
Particle Swarm Optimization Algorithm
Pattern Search Algorithm
Population Set
Python algorithm implementation
Python code
scientific computing methods
Search Agents
Search Space
Shuffled Frog Leaping Algorithm
Swarm Intelligence
Teaching Learning Based Optimization Algorithm
Tentative Solution

Product details

  • ISBN 9781032544151
  • Weight: 660g
  • Dimensions: 156 x 234mm
  • Publication Date: 11 Oct 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming.

These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in.

Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.
About Babak Zolghadr-Asli

Babak Zolghadr-Asli is currently a joint researcher under the QUEX program, working at the Sustainable Minerals Institute at The University of Queensland in Australia and The Centre for Water Systems at The University of Exeter in the UK. His primary research interest is to incorporate computational and artificial intelligence to understand the sustainable management of water resources.

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