An enhanced pathfinder algorithm for engineering optimization problems

The pathfinder algorithm (PFA) is a new population-based optimizer, it divides the search agents of the algorithm into leaders and followers, imitating the leadership level of the group movement to find the best food area or prey. In PFA, followers follow the new position according to the position of the leader and their own consciousness makes the algorithm easy to fall into local optimum. To overcome this shortcoming, the following stage is complicated in this paper, and the acceptance operator, the exchange operator and the mutation mechanism are introduced into the algorithm. To further balance the mining ability and exploration ability of the algorithm, the article regards the leader as a guide and introduces a guide mechanism. To verify the performance of the improved algorithm, it is applied to nine real-life engineering case problems. The simulation results of the real-life engineering design problems exhibit the superiority of the improved PFA (IMPFA) algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic PFA algorithm or other available solutions.

Automated summary

The Pathfinder Algorithm (PFA) is a new population-based optimizer that divides search agents into leaders and followers. To avoid falling into local optima, acceptance, exchange, and mutation mechanisms are introduced. By treating the leader as a guide and introducing a guidance mechanism, the algorithm's mining and exploration capabilities are balanced.