Treffer: Evaluating the performance of meta-heuristic algorithms on CEC 2021 benchmark problems

Title:
Evaluating the performance of meta-heuristic algorithms on CEC 2021 benchmark problems
Authors:
Ali Wagdy Mohamed, Karam M. Sallam, Prachi Agrawal, Anas A. Hadi, Ali Khater Mohamed
Source:
Neural Computing and Applications. 35:1493-1517
Publisher Information:
Springer Science and Business Media LLC, 2022.
Publication Year:
2022
Subject Terms:
Optimization, Real-time Optimization, Artificial intelligence, Economics, 0211 other engineering and technologies, Heuristic, Metaheuristics, 02 engineering and technology, Task (project management), Engineering, Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Heuristics, Swarm Intelligence Optimization Algorithms, 10. No inequality, Constraint Handling, Numerical Analysis, Numerical Optimization Techniques, Arithmetic, Geography, Optimization Applications, Mathematical optimization, Meta heuristic, 16. Peace & justice, Computer science, Management, Algorithm, Parameterized complexity, Operating system, Model Predictive Control in Industrial Processes, Control and Systems Engineering, Computer Science, Physical Sciences, Benchmark (surveying), Binary number, Mathematics, Geodesy
Document Type:
Fachzeitschrift Article<br />Other literature type
Language:
English
ISSN:
1433-3058
0941-0643
DOI:
10.1007/s00521-022-07788-z
DOI:
10.60692/d1es4-wr422
DOI:
10.60692/tm45r-saf98
Rights:
CC BY
Accession Number:
edsair.doi.dedup.....fee9f8e38d0ae5c0933f3a91048a1a2c
Database:
OpenAIRE

Weitere Informationen

To develop new meta-heuristic algorithms and evaluate on the benchmark functions is the most challenging task. In this paper, performance of the various developed meta-heuristic algorithms are evaluated on the recently developed CEC 2021 benchmark functions. The objective functions are parametrized by inclusion of the operators, such as bias, shift and rotation. The different combinations of the binary operators are applied to the objective functions which leads to the CEC2021 benchmark functions. Therefore, different meta-heuristic algorithms are considered which solve the benchmark functions with different dimensions. The performance of some basic, advanced meta-heuristics algorithms and the algorithms that participated in the CEC2021 competition have been experimentally investigated and many observations, recommendations, conclusions have been reached. The experimental results show the performance of meta-heuristic algorithms on the different combinations of binary parameterized operators.