The current work aims at developing an efficient methodology based on pathfinder algorithm (PFA) to study and examine the dynamic performances of fuel cells. At initial stage of this work, the uncertain parameters of fuel cells are defined by using the PFA complete with necessary discussions, ...
Hybridization of metaheuristic algorithms with local search has been investigated in many studies. This paper proposes a hybrid pathfinder algorithm (HPFA), which incorporates the mutation operator i...
Pathfinder algorithmThis paper proposes a new meta-heuristic algorithm called Pathfinder Algorithm (PFA) to solve optimization problems with different structure. This method is inspired by collective movement of animal group and mimics the leadership hierarchy of swarms to find best food area or prey...
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...
Pathfinder algorithm (PFA) is a swarm intelligent optimization algorithm inspired by the collective activity behavior of swarm animals, imitating the leader in the population to guide followers in finding the best food source. This algorithm has the characteristics of a simple structure and high ...
It is optimized by a recent metaheuristic optimizer called pathfinder algorithm (PFA). An interconnected two-area power system model comprising of multi-sources like thermal, hydro and gas generating units including physical constraints namely, governor dead band (GDB) and generation rate constraint (...
pathfinder algorithmstatistical testsThe optimal reactive power dispatch (ORPD) problem, as a subproblem of optimal power flow, has significant effects in providing reliability and economic operation. In this article, a modified version of the pathfinder algorithm (PFA), which is inspired by the ...
The pathfinder algorithm (PFA) starts with a random search for the initial population, which is then partitioned into only a pathfinder phase and a follower phase. This approach often results in issues like poor solution accuracy, slow convergence, and susceptibility to local optima...
ASDR-PFA algorithmOptimal feature selectionPathfinder algorithm (PFA) is a recently introduced meta-heuristic technique that mimics the cooperative behavior of animal groups in search of the best food area. PFA consists of two phases, namely, the path-finder phase and the follower phase. The ...
They represent the exploration phase and mining phase of PFA respectively. However, the original algorithm also has the problem of falling into a local optimum. In order to solve this problem, the teaching phase in the teaching and learning algorithm is added to the pathfinder stage in the ...