Particle Swarm Optimization Algorithm Based on Information Sharing in Industry 4.0

Algorithm 1

The framework of IPSO (searching the minimum value).

	Step 1: randomly generate particles and give the velocity and location of each particle.
	Step 2: evaluate each particle using the fitness value.
	Step 3: for each particle,
	If the fitness value of the particle is less than the best particle’s fitness value of , update its location with .
	Otherwise, if the fitness value of the particle is greater than the worst particle’s fitness value , update its location .
	Step 4: for each particle,
	If the fitness value of the particle is less than the best fitness value of the entire swarm, update the value of using this particle’s fitness value.
	Otherwise, if the fitness value of the particle is greater than the worst fitness value of the entire swarm, update the worst fitness value of the entire swarm using this particle’s fitness value.
	Step 5: for each particle,
(1)	Generate this particle’s active flight direction using (1) and (2).
(2)	Generate this particle’s passive flight direction using (13) and (14).
(3)	Compare and , and choose the best of them to update this particle.
	Step 6: repeat Step 2 until you find the optimal solution or satisfy the termination condition.