A Novel Modified Swarm Intelligence Algorithm Combining Black Widow Optimization Algorithm and Pelican Optimization Algorithm to solve Global Optimization Problems

作者
Ayad Hamad Khalaf
标识
DOI:10.47134/ppm.v2i2.1480
摘要

In this paper, an improved algorithm called BWOA-POA is a hybrid algorithm based on the Black Widow Algorithm (BWOA), which is an algorithm inspired by nature and has excellent specifications in addition to another algorithm, the Pelican Swarm Optimization Algorithm (POA), which is a smart swarm algorithm that is also inspired by nature When studying these two algorithms, we find that each of them has some weaknesses and that they fall into local solutions in some countries and this is what prompted us to develop the hybrid algorithm BWOA- POA, which was able to avoid falling into the trap of local solutions and reach the global optimal solution, as the numerical results proved its superiority over the others and the speed of reaching the solution in record time with the least number of swarm elements and the least number of iterations, as this developed algorithm BWOA-POA was applied to the optimality measurement functions and the results were excellent if compared with its predecessors, This model is one of the most powerful models and can be applied in solving engineering problems and all studies that need to reach the best solutions from minimizing or maximizing the models presented.

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