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While both have performances ranging from 77 to 100%, CS aces all ten standard optimization benchmarks, where each algorithm has been run at least 100 times so as to carry out meaningful statistical analysis.
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The IEEE CEC'2013 large-scale global optimization benchmark suite [29] is one such implementation.
Results are obtained from standard optimization benchmark functions and the traveling salesman problem (TSP).
Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration.
MDQL has been previously tested on several multi-objective optimization benchmark problems with promising results [C.
Eight numerical multi-objective optimization benchmark problems are solved to demonstrate the efficiency and robustness of the proposed algorithm.
It is observed that JAYA algorithm seems to be an efficient one in solving the constrained and unconstrained optimization benchmark problems.
In this paper, 23 optimization benchmark problems with different characteristics and four other engineering problems are employed to evaluate the performance of the proposed SA-MFO algorithm.
To judge the performance of the algorithm, we have solved aset of constrained optimization benchmark problems, as well as 14 well-known engineering optimization problems.
The performance of proposed approach named as PSOd is investigated on solving 13 nonlinear global optimization benchmark functions and three constrained engineering optimization problems.
We hybridized the standard FPA with the Clonal Selection Algorithm (CSA) and tested the new algorithm by applying it to 23 optimization benchmark problems.
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