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MATLAB Codes of Metaheuristics Methods
https://orcid.org/https://orcid.org/0000-0001-9106-0313
This chapter showcases the implementation of ten metaheuristic algorithms using MATLAB for solving truss optimization problems. Algorithms like the dragonfly algorithm, the multiverse optimizer, the sine cosine algorithm, the whale optimization algorithm, the ant lion optimizer, the heat transfer search, the passing vehicle search, the symbiotic organisms search, the grey wolf optimizer, and the teaching-learning-based optimization are presented and applied to truss optimization problems. This collection of MATLAB implementations demonstrates the practicality and versatility of these metaheuristic methods, offering engineers and researchers valuable tools for tackling complex engineering challenges.
MATLAB Codes of Metaheuristics Methods
https://orcid.org/https://orcid.org/0000-0001-9106-0313
This chapter showcases the implementation of ten metaheuristic algorithms using MATLAB for solving truss optimization problems. Algorithms like the dragonfly algorithm, the multiverse optimizer, the sine cosine algorithm, the whale optimization algorithm, the ant lion optimizer, the heat transfer search, the passing vehicle search, the symbiotic organisms search, the grey wolf optimizer, and the teaching-learning-based optimization are presented and applied to truss optimization problems. This collection of MATLAB implementations demonstrates the practicality and versatility of these metaheuristic methods, offering engineers and researchers valuable tools for tackling complex engineering challenges.
MATLAB Codes of Metaheuristics Methods
https://orcid.org/https://orcid.org/0000-0001-9106-0313
This chapter showcases the implementation of ten metaheuristic algorithms using MATLAB for solving truss optimization problems. Algorithms like the dragonfly algorithm, the multiverse optimizer, the sine cosine algorithm, the whale optimization algorithm, the ant lion optimizer, the heat transfer search, the passing vehicle search, the symbiotic organisms search, the grey wolf optimizer, and the teaching-learning-based optimization are presented and applied to truss optimization problems. This collection of MATLAB implementations demonstrates the practicality and versatility of these metaheuristic methods, offering engineers and researchers valuable tools for tackling complex engineering challenges.
MATLAB Codes of Metaheuristics Methods
Savsani, Vimal (author) / Tejani, Ghanshyam (author) / Patel, Vivek (author)
Truss Optimization ; Chapter: 8 ; 385-425
2024-02-17
41 pages
Article/Chapter (Book)
Electronic Resource
English
MATLAB , Dragonfly algorithm , Multi-verse optimizer , Sine cosine algorithm , Whale optimization algorithm , Ant lion optimizer , Heat transfer search , Passing vehicle search , Symbiotic organisms search , Grey wolf optimizer , Teaching-learning based optimization Engineering , Mechanical Statics and Structures , Light Construction, Steel Construction, Timber Construction , Solid Construction , Structural Materials , Civil Engineering
| Springer Verlag | 2024
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