An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem

Algorithm 2

M-PSO.

	Input: nmax: the threshold to find local extremal, tmax: number of evolution generations.
	Output: the best solution gbest
(1)	Begin
(2)	Pall ← Init data from iMOPSE dataset and create population.
(3)	t = 0
(4)	nf = 0
(5)	while (t < tmax)
(6)	t = t + 1
(7)	for i = 1 to size (Pall) do
(8)	Calculate the objective value: f (Pi)
(9)	end for
(10)	for i = 1 to size (Pall) do
(11)	if f (Pi) < f (fitnessi) then
(12)	pbesti = Pi
(13)	f (pbesti) = f (Pi)
(14)	end if
(15)	end for
(16)	for i = 1 to size (Pall) do
(17)	if (f (Pi) < f (gbest)) then
(18)	gbest = Pi
(19)	f (gbest) = f (Pi)
(20)	end if
(21)	if f(Pi)! = f(Pi-1) then
(22)	nf = 0
(23)	else
(24)	nf + = 1
(25)	end if
(26)	end for
(27)	for i = 1 to size (Pall) do
(28)	update velocity vector
(29)	update position vector
(30)	end for
(31)	if (nf = nmax)
(32)	Pall ← Migration (Pall)
(33)	nf = 0
(34)	end if
(35)	end while
(36)	return gbest
(37)	end
	f: objective function