  This study presents the vectorization of metaheuristic algorithms as the
first stage of vectorized optimization implementation. Vectorization is a
technique for converting an algorithm, which operates on a single value at a
time to one that operates on a collection of values at a time to execute
rapidly. The vectorization technique also operates by replacing multiple
iterations into a single operation, which improves the algorithm's performance
in speed and makes the algorithm simpler and easier to be implemented. It is
important to optimize the algorithm by implementing the vectorization
technique, which improves the program's performance, which requires less time
and can run long-running test functions faster, also execute test functions
that cannot be implemented in non-vectorized algorithms and reduces iterations
and time complexity. Converting to vectorization to operate several values at
once and enhance algorithms' speed and efficiency is a solution for long
running times and complicated algorithms. The objective of this study is to use
the vectorization technique on one of the metaheuristic algorithms and compare
the results of the vectorized algorithm with the algorithm which is
non-vectorized.
