Inspiration

A pathfinder simply is the individual which leads a swarm. This entity leads the swarm and this entity leads various acts. In addition, this entity takes the swarm to destinations including pastures, water and feeding areas. The group of animals frequently decide the movement between members via social order. Such animals may either have to decide with the leader or with no leader. Leadership however is temporary, with few people knowing the place, hunting area, route, etc.

Pathfinder Optimization Algorithm

Nature is full of social behaviours for performing different tasks. Although the ultimate goal of all individuals and collective behaviours is survival, creatures cooperate and interact in groups, herds, schools, colonies, and flocks for several reasons: hunting, defending, navigating, and foraging. In order to mimic these characteristics of animals, swarm-intelligence based optimization algorithms are introduced.

Similar Reads

Inspiration

A pathfinder simply is the individual which leads a swarm. This entity leads the swarm and this entity leads various acts. In addition, this entity takes the swarm to destinations including pastures, water and feeding areas. The group of animals frequently decide the movement between members via social order. Such animals may either have to decide with the leader or with no leader. Leadership however is temporary, with few people knowing the place, hunting area, route, etc....

Mathematical Model

The population basically follows the pathfinder for various activities. However, in order to do so, we need to specify the position of both the pathfinder and any arbitrary population member. The position of a member says Xi is defined as:...

Algorithm

Define the parameters such as r1, r2, ε, AInitialize the population and calculate fitness for each memberSet the best fitness value as the pathfinderwhile iteration condition is not met or till max iteration doGenerate α, ß in range [0, 1]Using the pathfinder equation update the position of pathfinderIf fitness of current pathfinder is better than old pathfinder ThenUpdate fitness of the pathfinderFor i=1 to population sizeUpdate position of followers using followers equation.Update fitness values of each memberFind the best fitnessIf best fitness is better than old pathfinder ThenUpdate fitness of the pathfinderFor i=1 to population sizeIf new fitness of the member is better than old fitness ThenUpdate fitness of memberGenerate ε, AEnd...