Tuna Swarm Optimization: A Novel Swarm-Based Metaheuristic Algorithm for Global Optimization

Algorithm 1

Pseudocode of TSO.

	Input: the population size NP and maximum iteration tmax
Output: the location of food (the best individual) and its fitness value
Initialize the random population of tunas (i = 1, 2, . . ., NP)
Assign free parameters a and z
While (t < tmax)
Calculate the fitness values of tunas
Update
For (each tuna) do
Update , ,
If () then
Update the position using equation (1)
Else if () then
If () then
If () then
Update the position using Equation (7)
Else if () then
Update the position using Equation (2)
Else if () then
Update the position using Equation (9)
End for
End while
Return the best individual and the best fitness value .