Path Planning of Slab Library Crane Based on Improved Ant Colony Algorithm

Algorithm 1

Implementation process of Crane path planning based on CP-ACA.

	Initialize the population size of , which are placed on the grid node of the starting point, and the total iterations .
	Initialize of the CP-ACA.
	Initialize pheromone intensity, walking distance and heuristic function among the nodes on the path.
	While () or (the stop criterion is not met)
	For each ant and the target point is not obtained;
	Accord to the performance requirements for the big car and little car, the grid node set for moving is extracted with the current node as the center;
	Accord to the equipment constraint of the slab library, the grid node is filtered from ;
	Obtain the heuristic function according to formula (4);
	The next node is selected from the candidate grid node set by formula (1);
	End for
	For each ant
	Calculate the walking distance of each ant to complete the travel in this iteration ;
	Calculate the number of turning points in the walking path of each ant;
	Update the increment of pheromone intensity by formula (5);
	End for
	Update the pheromone intensity between the nodes in slab library according to formula (7);
	t = t + 1;
	End while
	Return